Closed Dartvauder closed 1 month ago
william-murray1204
commented
1 month ago Hi @Dartvauder, thanks for your interest in the project. I have just updated the package to use the latest stable-diffusion.cpp version. You should now be able to use FLUX models without issue on stable-diffusion-cpp-python version 0.1.7 and onwards.
Dartvauder
commented
1 month ago Hi @Dartvauder, thanks for your interest in the project. I have just updated the package to use the latest stable-diffusion.cpp version. You should now be able to use FLUX models without issue on stable-diffusion-cpp-python version 0.1.7 and onwards.
Amazing! I will try it soon. Honestly, I did not expect you to do it so quickly. Thank you very much.
Dartvauder
commented
1 month ago Hi @Dartvauder, thanks for your interest in the project. I have just updated the package to use the latest stable-diffusion.cpp version. You should now be able to use FLUX models without issue on stable-diffusion-cpp-python version 0.1.7 and onwards.
@william-murray1204 i tried to run flux1-dev-Q6_K.gguf and I got this error
stable-diffusion.cpp:180 - Using CPU backend stable-diffusion.cpp:195 - loading model from 'inputs\image\quantize-flux\flux1-dev-Q6_K.gguf' model.cpp:790 - load inputs\image\quantize-flux\flux1-dev-Q6_K.gguf using gguf format model.cpp:807 - init from 'inputs\image\quantize-flux\flux1-dev-Q6_K.gguf' stable-diffusion.cpp:231 - get sd version from file failed: 'inputs\image\quantize-flux\flux1-dev-Q6_K.gguf' Traceback (most recent call last): File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\queueing.py", line 536, in process_events response = await route_utils.call_process_api( File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\route_utils.py", line 321, in call_process_api output = await app.get_blocks().process_api( File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1935, in process_api result = await self.call_function( File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1520, in call_function prediction = await anyio.to_thread.run_sync( # type: ignore File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync return await get_async_backend().run_sync_in_worker_thread( File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio_backends_asyncio.py", line 2144, in run_sync_in_worker_thread return await future File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio_backends_asyncio.py", line 851, in run result = context.run(func, args) File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\utils.py", line 826, in wrapper response = f(args, **kwargs) File "C:\Coding\Python\NeuroSandboxWebUI\LaunchFiles\appEN.py", line 4119, in generate_image_flux if enable_quantize: UnboundLocalError: local variable 'stable_diffusion' referenced before assignment
If it is interesting and important to see what the part of the code that is responsible for working with flux looks like (to understand maybe I am doing something wrong)
Here is the main function without interface:
def generate_image_flux(prompt, model_name, quantize_model_name, enable_quantize, lora_model_names, lora_scales, guidance_scale, height, width, num_inference_steps, max_sequence_length, seed, output_format="png"):
device = "cuda" if torch.cuda.is_available() else "cpu"
if seed == "" or seed is None:
seed = random.randint(0, 2 ** 32 - 1)
else:
seed = int(seed)
generator = torch.Generator(device).manual_seed(seed)
if not model_name:
return None, "Please select a Flux model!"
flux_model_path = os.path.join("inputs", "image", "flux", model_name)
if not os.path.exists(flux_model_path):
print(f"Downloading Flux {model_name} model...")
os.makedirs(flux_model_path, exist_ok=True)
Repo.clone_from(f"https://huggingface.co/black-forest-labs/{model_name}", flux_model_path)
print(f"Flux {model_name} model downloaded")
try:
if enable_quantize:
quantize_flux_model_path = os.path.join("inputs", "image", "quantize-flux", f"{quantize_model_name}.gguf")
lora_model_path = os.path.join("inputs", "image", "flux-lora", f"{lora_model_names}.safetensors")
stable_diffusion = StableDiffusion(
model_path=quantize_flux_model_path,
lora_model_dir=lora_model_path,
wtype="default")
output = stable_diffusion.txt_to_img(
prompt=prompt,
guidance=guidance_scale,
height=height,
width=width,
sample_steps=num_inference_steps,
seed=seed)
else:
pipe = FluxPipeline.from_pretrained(flux_model_path, torch_dtype=torch.bfloat16)
pipe.to(device)
pipe.enable_model_cpu_offload()
pipe.enable_sequential_cpu_offload()
pipe.vae.enable_slicing()
pipe.vae.enable_tiling()
pipe.to(torch.float16)
if isinstance(lora_scales, str):
lora_scales = [float(scale.strip()) for scale in lora_scales.split(',') if scale.strip()]
elif isinstance(lora_scales, (int, float)):
lora_scales = [float(lora_scales)]
lora_loaded = False
if lora_model_names and lora_scales:
if len(lora_model_names) != len(lora_scales):
print(
f"Warning: Number of LoRA models ({len(lora_model_names)}) does not match number of scales ({len(lora_scales)}). Using available scales.")
for i, lora_model_name in enumerate(lora_model_names):
if i < len(lora_scales):
lora_scale = lora_scales[i]
else:
lora_scale = 1.0
lora_model_path = os.path.join("inputs", "image", "flux-lora", lora_model_name)
if os.path.exists(lora_model_path):
adapter_name = os.path.splitext(os.path.basename(lora_model_name))[0]
try:
pipe.load_lora_weights(lora_model_path, adapter_name=adapter_name)
pipe.fuse_lora(lora_scale=lora_scale)
lora_loaded = True
print(f"Loaded LoRA {lora_model_name} with scale {lora_scale}")
except Exception as e:
print(f"Error loading LoRA {lora_model_name}: {str(e)}")
output = pipe(
prompt=prompt,
guidance_scale=guidance_scale,
height=height,
width=width,
num_inference_steps=num_inference_steps,
max_sequence_length=max_sequence_length,
generator=generator
).images[0]
today = datetime.now().date()
image_dir = os.path.join('outputs', f"Flux_{today.strftime('%Y%m%d')}")
os.makedirs(image_dir, exist_ok=True)
image_filename = f"flux_{datetime.now().strftime('%Y%m%d_%H%M%S')}.{output_format}"
image_path = os.path.join(image_dir, image_filename)
output.save(image_path, format=output_format.upper())
return image_path, f"Image generated successfully. Seed used: {seed}"
except Exception as e:
return None, str(e)
finally:
if enable_quantize:
del stable_diffusion
else:
del pipe
flush()I've updated the README.md to include FLUX usage docs.
Essentially, FLUX models should be run using the same implementation as the stable-diffusion.cpp FLUX documentation where the diffusion_model_path argument is used in place of the model_path. I believe the clip_l_path, t5xxl_path, and vae_path arguments are also required for inference to function (download links are provided in the README.md and in the stable-diffusion.cpp FLUX documentation).
Your code would look something like this:
from stable_diffusion_cpp import StableDiffusion
...
stable_diffusion = StableDiffusion(
diffusion_model_path=quantize_flux_model_path, # in place of model_path
clip_l_path="../models/clip_l.safetensors",
t5xxl_path="../models/t5xxl_fp16.safetensors",
vae_path="../models/ae.safetensors",
lora_model_dir=lora_model_path,
wtype="default",
)
output = stable_diffusion.txt_to_img(
prompt=prompt,
guidance=guidance_scale,
height=height,
width=width,
sample_steps=num_inference_steps,
seed=seed,
cfg_scale=1.0, # a cfg_scale of 1 is recommended for FLUX
sample_method="euler", # euler is recommended for FLUX
)I've updated the README.md to include FLUX usage docs.
Essentially, FLUX models should be run using the same implementation as the stable-diffusion.cpp FLUX documentation where the
diffusion_model_pathargument is used in place of themodel_path. I believe theclip_l_path,t5xxl_path, andvae_patharguments are also required for inference to function (download links are provided in the README.md and in the stable-diffusion.cpp FLUX documentation).Your code would look something like this:
from stable_diffusion_cpp import StableDiffusion ... stable_diffusion = StableDiffusion( diffusion_model_path=quantize_flux_model_path, # in place of model_path clip_l_path="../models/t5xxl_fp16.safetensors", t5xxl_path="../models/clip_l.safetensors", vae_path="../models/ae.safetensors", lora_model_dir=lora_model_path, wtype="default", ) output = stable_diffusion.txt_to_img( prompt=prompt, guidance=guidance_scale, height=height, width=width, sample_steps=num_inference_steps, seed=seed, cfg_scale=1.0, # a cfg_scale of 1 is recommended for FLUX sample_method="euler", # euler is recommended for FLUX )
I just tried what you showed and did it like this:
if enable_quantize:
quantize_flux_model_path = os.path.join("inputs", "image", "quantize-flux", f"{quantize_model_name}.gguf")
lora_model_path = os.path.join("inputs", "image", "flux-lora", f"{lora_model_names}.safetensors")
if not quantize_model_name:
return None, "Please select a quantize Flux model!"
stable_diffusion = StableDiffusion(
diffusion_model_path=quantize_flux_model_path,
clip_l_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors",
t5xxl_path="inputs/image/quantize-flux/clip_l.safetensors",
vae_path="inputs/image/quantize-flux/ae.safetensors",
lora_model_dir=lora_model_path,
wtype="default")
output = stable_diffusion.txt_to_img(
prompt=prompt,
cfg_scale=guidance_scale,
height=height,
width=width,
sample_steps=num_inference_steps,
seed=seed,
sample_method="euler")stable-diffusion.cpp:180 - Using CPU backend
stable-diffusion.cpp:202 - loading clip_l from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/t5xxl_fp16.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
stable-diffusion.cpp:209 - loading t5xxl from 'inputs/image/quantize-flux/clip_l.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/clip_l.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/clip_l.safetensors'
stable-diffusion.cpp:216 - loading diffusion model from 'inputs\image\quantize-flux\flux1-dev-Q6_K.gguf'
model.cpp:790 - load inputs\image\quantize-flux\flux1-dev-Q6_K.gguf using gguf format
model.cpp:807 - init from 'inputs\image\quantize-flux\flux1-dev-Q6_K.gguf'
stable-diffusion.cpp:223 - loading vae from 'inputs/image/quantize-flux/ae.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/ae.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/ae.safetensors'
stable-diffusion.cpp:235 - Version: Flux Dev
stable-diffusion.cpp:266 - Weight type: f16
stable-diffusion.cpp:267 - Conditioner weight type: f16
stable-diffusion.cpp:268 - Diffusion model weight type: q6_K
stable-diffusion.cpp:269 - VAE weight type: f32
stable-diffusion.cpp:271 - ggml tensor size = 400 bytes
clip.hpp:171 - vocab size: 49408
clip.hpp:182 - trigger word img already in vocab
ggml_extend.hpp:1050 - clip params backend buffer size = 235.06 MB(RAM) (196 tensors)
ggml_extend.hpp:1050 - t5 params backend buffer size = 9083.77 MB(RAM) (219 tensors)
ggml_extend.hpp:1050 - flux params backend buffer size = 9320.55 MB(RAM) (780 tensors)
ggml_extend.hpp:1050 - vae params backend buffer size = 160.00 MB(RAM) (244 tensors)
stable-diffusion.cpp:398 - loading weights
model.cpp:1530 - loading tensors from inputs/image/quantize-flux/t5xxl_fp16.safetensors
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.0.SelfAttention.relative_attention_bias.weight | f16 | 2 [64, 32, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.0.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.1.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.10.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.11.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.12.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.13.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.14.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.15.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.16.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.17.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.18.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.19.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.2.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.20.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.21.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.22.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.23.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.3.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.4.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.5.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.6.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.7.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.8.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.0.SelfAttention.k.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.0.SelfAttention.o.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.0.SelfAttention.q.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.0.SelfAttention.v.weight | f16 | 2 [4096, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.0.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.1.DenseReluDense.wi_0.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.1.DenseReluDense.wi_1.weight | f16 | 2 [4096, 10240, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.1.DenseReluDense.wo.weight | f16 | 2 [10240, 4096, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.block.9.layer.1.layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.embed_tokens.weight | f16 | 2 [4096, 32128, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.encoder.final_layer_norm.weight | f16 | 1 [4096, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.clip_l.shared.weight | f16 | 2 [4096, 32128, 1, 1, 1]' in model file
model.cpp:1530 - loading tensors from inputs/image/quantize-flux/clip_l.safetensors
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.embeddings.position_embedding.weight | f16 | 2 [768, 77, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.embeddings.token_embedding.weight | f16 | 2 [768, 49408, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.0.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.1.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.10.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.11.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.2.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.3.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.4.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.5.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.6.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.7.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.8.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.layer_norm1.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.layer_norm1.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.layer_norm2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.layer_norm2.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.mlp.fc1.bias | f16 | 1 [3072, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.mlp.fc1.weight | f16 | 2 [768, 3072, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.mlp.fc2.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.mlp.fc2.weight | f16 | 2 [3072, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.self_attn.k_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.self_attn.k_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.self_attn.out_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.self_attn.out_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.self_attn.q_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.self_attn.q_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.self_attn.v_proj.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.encoder.layers.9.self_attn.v_proj.weight | f16 | 2 [768, 768, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.final_layer_norm.bias | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.text_model.final_layer_norm.weight | f16 | 1 [768, 1, 1, 1, 1]' in model file
model.cpp:1530 - loading tensors from inputs\image\quantize-flux\flux1-dev-Q6_K.gguf
model.cpp:1530 - loading tensors from inputs/image/quantize-flux/ae.safetensors
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.embeddings.position_embedding.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.embeddings.token_embedding.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.0.layer_norm1.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.0.layer_norm1.weight' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.0.mlp.fc1.bias' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.0.mlp.fc2.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.0.self_attn.k_proj.bias' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.0.self_attn.out_proj.bias' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.0.self_attn.q_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.0.self_attn.q_proj.weight' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.layer_norm1.bias' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.layer_norm2.bias' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.mlp.fc2.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.mlp.fc2.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.self_attn.k_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.self_attn.k_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.self_attn.out_proj.bias' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.self_attn.q_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.self_attn.q_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.1.self_attn.v_proj.bias' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.layer_norm1.bias' not in model file
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model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.layer_norm2.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.layer_norm2.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.mlp.fc1.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.mlp.fc1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.mlp.fc2.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.mlp.fc2.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.self_attn.k_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.self_attn.k_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.self_attn.out_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.self_attn.out_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.self_attn.q_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.self_attn.q_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.self_attn.v_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.10.self_attn.v_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.layer_norm1.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.layer_norm1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.layer_norm2.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.layer_norm2.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.mlp.fc1.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.mlp.fc1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.mlp.fc2.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.mlp.fc2.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.self_attn.k_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.self_attn.k_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.self_attn.out_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.self_attn.out_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.self_attn.q_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.self_attn.q_proj.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.self_attn.v_proj.bias' not in model file
model.cpp:1729 - tensor 'text_encoders.clip_l.text_model.encoder.layers.11.self_attn.v_proj.weight' not in model file
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model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.13.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.14.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.15.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.16.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.17.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.18.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.19.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.2.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.20.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.21.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.22.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.23.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.3.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.4.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.5.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.6.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.7.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.8.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.0.SelfAttention.k.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.0.SelfAttention.o.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.0.SelfAttention.q.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.0.SelfAttention.v.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.0.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.1.DenseReluDense.wi_0.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.1.DenseReluDense.wi_1.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.1.DenseReluDense.wo.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.block.9.layer.1.layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.encoder.final_layer_norm.weight' not in model file
model.cpp:1729 - tensor 'text_encoders.t5xxl.shared.weight' not in model file
stable-diffusion.cpp:420 - load tensors from model loader failed
Traceback (most recent call last):
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\queueing.py", line 536, in process_events
response = await route_utils.call_process_api(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\route_utils.py", line 321, in call_process_api
output = await app.get_blocks().process_api(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1935, in process_api
result = await self.call_function(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1520, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2144, in run_sync_in_worker_thread
return await future
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
result = context.run(func, *args)
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\utils.py", line 826, in wrapper
response = f(*args, **kwargs)
File "C:\Coding\Python\NeuroSandboxWebUI\LaunchFiles\appEN.py", line 4047, in generate_image_flux
stable_diffusion = StableDiffusion(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\stable_diffusion_cpp\stable_diffusion.py", line 122, in __init__
self._model = _StableDiffusionModel(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\stable_diffusion_cpp\_internals.py", line 104, in __init__
raise ValueError(f"Failed to load model from file: {model_path}")
ValueError: Failed to load model from file:
The only thing I noticed is in the README.md file. You use output = stable_diffusion.flux_img, when i use output = stable_diffusion.txt_to_img. I tried to do it with output = stable_diffusion.flux_img and I get this error: Unresolved attribute reference 'flux_img' for class 'StableDiffusion'
william-murray1204
commented
1 month ago It looks like I mixed up the clip_l_path and t5xxl_path in the docs.
Try this instead:
stable_diffusion = StableDiffusion(
diffusion_model_path=quantize_flux_model_path,
clip_l_path="inputs/image/quantize-flux/clip_l.safetensors",
t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors",
vae_path="inputs/image/quantize-flux/ae.safetensors",
lora_model_dir=lora_model_path,
wtype="default"
)You are right in using stable_diffusion.txt_to_img for FLUX. There is no function called stable_diffusion.flux_img, that's just a silly mistake I made when writing up the docs. It is now fixed.
Dartvauder
commented
1 month ago It looks like I mixed up the
clip_l_pathandt5xxl_pathin the docs.Try this instead:
stable_diffusion = StableDiffusion( diffusion_model_path=quantize_flux_model_path, clip_l_path="inputs/image/quantize-flux/clip_l.safetensors", t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors", vae_path="inputs/image/quantize-flux/ae.safetensors", lora_model_dir=lora_model_path, wtype="default" )You are right in using
stable_diffusion.txt_to_imgfor FLUX. There is no function calledstable_diffusion.flux_img, that's just a silly mistake I made when writing up the docs. It is now fixed.
I did as you said and it worked for me so slow. But I noticed that I was using CPU backend. I deleted and cleared cache of everything related to this library and reinstalled it with these parameters:
# requirements.txt
pip install stable-diffusion-cpp-python -C cmake.args="-DSD_CUBLAS=on"This time my installation took more than 10 minutes. I start the generation again and now I get this error when Using CUDA backend:
stable-diffusion.cpp:157 - Using CUDA backend
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes
stable-diffusion.cpp:202 - loading clip_l from 'inputs/image/quantize-flux/clip_l.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/clip_l.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/clip_l.safetensors'
stable-diffusion.cpp:209 - loading t5xxl from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/t5xxl_fp16.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
stable-diffusion.cpp:216 - loading diffusion model from 'inputs\image\quantize-flux\flux1-dev-Q6_K.gguf'
model.cpp:790 - load inputs\image\quantize-flux\flux1-dev-Q6_K.gguf using gguf format
model.cpp:807 - init from 'inputs\image\quantize-flux\flux1-dev-Q6_K.gguf'
stable-diffusion.cpp:223 - loading vae from 'inputs/image/quantize-flux/ae.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/ae.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/ae.safetensors'
stable-diffusion.cpp:235 - Version: Flux Dev
stable-diffusion.cpp:266 - Weight type: f16
stable-diffusion.cpp:267 - Conditioner weight type: f16
stable-diffusion.cpp:268 - Diffusion model weight type: q6_K
stable-diffusion.cpp:269 - VAE weight type: f32
stable-diffusion.cpp:271 - ggml tensor size = 400 bytes
stable-diffusion.cpp:310 - set clip_on_cpu to true
stable-diffusion.cpp:313 - CLIP: Using CPU backend
clip.hpp:171 - vocab size: 49408
clip.hpp:182 - trigger word img already in vocab
ggml_extend.hpp:1050 - clip params backend buffer size = 235.06 MB(RAM) (196 tensors)
ggml_extend.hpp:1050 - t5 params backend buffer size = 9083.77 MB(RAM) (219 tensors)
Traceback (most recent call last):
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\queueing.py", line 536, in process_events
response = await route_utils.call_process_api(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\route_utils.py", line 321, in call_process_api
output = await app.get_blocks().process_api(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1935, in process_api
result = await self.call_function(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1520, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2144, in run_sync_in_worker_thread
return await future
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
result = context.run(func, *args)
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\utils.py", line 826, in wrapper
response = f(*args, **kwargs)
File "C:\Coding\Python\NeuroSandboxWebUI\LaunchFiles\appEN.py", line 4043, in generate_image_flux
stable_diffusion = StableDiffusion(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\stable_diffusion_cpp\stable_diffusion.py", line 122, in __init__
self._model = _StableDiffusionModel(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\stable_diffusion_cpp\_internals.py", line 79, in __init__
self.model = sd_cpp.new_sd_ctx(
OSError: exception: access violation reading 0x0000000000000000What could be the problem?
william-murray1204
commented
1 month ago Unfortunately, I cant seem to replicate the error. Are you on Linux or Mac? Could you run nvcc --version and send me what is returned?
Do you also encounter the error when running a simple implementation of the code with the arguments hardcoded. For example, running the following file using python test.py:
# test.py
from stable_diffusion_cpp import StableDiffusion
stable_diffusion = StableDiffusion(
diffusion_model_path="inputs/image/quantize-flux/flux1-dev-Q6_K.gguf",
clip_l_path="inputs/image/quantize-flux/clip_l.safetensors",
t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors",
vae_path="inputs/image/quantize-flux/ae.safetensors",
)
output = stable_diffusion.txt_to_img(
prompt="a lovely cat holding a sign says 'flux.cpp'",
cfg_scale=1,
sample_steps=4,
sample_method="euler",
)
output[0].save("output.png")My suggestion would be to build stable-diffusion.cpp directly (specifically building for CUBLAS), then try to generate FLUX images using the same model weights and arguments but with the stable-diffusion.cpp CLI. That way you can take advantage of extra documentation and previous user issues in the stable-diffusion.cpp repo. It may help narrow down the issue to something specific such as a missing argument in CMAKE_ARGS. If you manage to build stable-diffusion.cpp for CUBLAS and can generate images without any errors, the problem is likely in my implementation of the Python bindings.
Let me know how you get on.
Dartvauder
commented
1 month ago Unfortunately, I cant seem to replicate the error. Are you on Linux or Mac? Could you run
nvcc --versionand send me what is returned?Do you also encounter the error when running a simple implementation of the code with the arguments hardcoded. For example, running the following file using
python test.py:# test.py from stable_diffusion_cpp import StableDiffusion stable_diffusion = StableDiffusion( diffusion_model_path="inputs/image/quantize-flux/flux1-dev-Q6_K.gguf", clip_l_path="inputs/image/quantize-flux/clip_l.safetensors", t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors", vae_path="inputs/image/quantize-flux/ae.safetensors", ) output = stable_diffusion.txt_to_img( prompt="a lovely cat holding a sign says 'flux.cpp'", cfg_scale=1, sample_steps=4, sample_method="euler", ) output[0].save("output.png")My suggestion would be to build stable-diffusion.cpp directly (specifically building for CUBLAS), then try to generate FLUX images using the same model weights and arguments but with the stable-diffusion.cpp CLI. That way you can take advantage of extra documentation and previous user issues in the stable-diffusion.cpp repo. It may help narrow down the issue to something specific such as a missing argument in
CMAKE_ARGS. If you manage to build stable-diffusion.cpp for CUBLAS and can generate images without any errors, the problem is likely in my implementation of the Python bindings.Let me know how you get on.
I am using Windows 11 64bit and this is what I got:
(venv) PS C:\Coding\Python\NeuroSandboxWebUI> nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2024 NVIDIA Corporation Built on Thu_Mar_28_02:30:10_Pacific_Daylight_Time_2024 Cuda compilation tools, release 12.4, V12.4.131 Build cuda_12.4.r12.4/compiler.34097967_0
I made a test.py file for these lines:
from stable_diffusion_cpp import StableDiffusion
stable_diffusion = StableDiffusion(
diffusion_model_path="inputs/image/quantize-flux/flux1-dev-Q6_K.gguf",
clip_l_path="inputs/image/quantize-flux/clip_l.safetensors",
t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors",
vae_path="inputs/image/quantize-flux/ae.safetensors",
)
output = stable_diffusion.txt_to_img(
prompt="a lovely cat holding a sign says 'flux.cpp'",
cfg_scale=4,
sample_steps=20,
sample_method="euler",
)
output[0].save("output.png")ran it and got this:
stable-diffusion.cpp:157 - Using CUDA backend
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes
stable-diffusion.cpp:202 - loading clip_l from 'inputs/image/quantize-flux/clip_l.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/clip_l.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/clip_l.safetensors'
stable-diffusion.cpp:209 - loading t5xxl from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/t5xxl_fp16.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
stable-diffusion.cpp:216 - loading diffusion model from 'inputs/image/quantize-flux/flux1-dev-Q6_K.gguf'
model.cpp:790 - load inputs/image/quantize-flux/flux1-dev-Q6_K.gguf using gguf format
model.cpp:807 - init from 'inputs/image/quantize-flux/flux1-dev-Q6_K.gguf'
stable-diffusion.cpp:223 - loading vae from 'inputs/image/quantize-flux/ae.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/ae.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/ae.safetensors'
stable-diffusion.cpp:235 - Version: Flux Dev
stable-diffusion.cpp:266 - Weight type: f16
stable-diffusion.cpp:267 - Conditioner weight type: f16
stable-diffusion.cpp:268 - Diffusion model weight type: q6_K
stable-diffusion.cpp:269 - VAE weight type: f32
stable-diffusion.cpp:271 - ggml tensor size = 400 bytes
stable-diffusion.cpp:310 - set clip_on_cpu to true
stable-diffusion.cpp:313 - CLIP: Using CPU backend
clip.hpp:171 - vocab size: 49408
clip.hpp:182 - trigger word img already in vocab
ggml_extend.hpp:1050 - clip params backend buffer size = 235.06 MB(RAM) (196 tensors)
ggml_extend.hpp:1050 - t5 params backend buffer size = 9083.77 MB(RAM) (219 tensors)
ggml_extend.hpp:1050 - flux params backend buffer size = 9320.56 MB(VRAM) (780 tensors)
ggml_extend.hpp:1050 - vae params backend buffer size = 160.00 MB(VRAM) (244 tensors)
stable-diffusion.cpp:398 - loading weights
model.cpp:1530 - loading tensors from inputs/image/quantize-flux/clip_l.safetensors
model.cpp:1530 - loading tensors from inputs/image/quantize-flux/t5xxl_fp16.safetensors
model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.encoder.embed_tokens.weight | f16 | 2 [4096, 32128, 1, 1, 1]' in model file
model.cpp:1530 - loading tensors from inputs/image/quantize-flux/flux1-dev-Q6_K.gguf
model.cpp:1530 - loading tensors from inputs/image/quantize-flux/ae.safetensors
stable-diffusion.cpp:497 - total params memory size = 18799.39MB (VRAM 9480.55MB, RAM 9318.83MB): clip 9318.83MB(RAM), unet 9320.56MB(VRAM), vae 160.00MB(VRAM), controlnet 0.00MB(VRAM), pmid 0.00MB(RAM)
stable-diffusion.cpp:501 - loading model from '' completed, taking 39.93s
stable-diffusion.cpp:518 - running in Flux FLOW mode
stable-diffusion.cpp:572 - finished loaded file
stable-diffusion.cpp:1378 - txt2img 512x512
stable-diffusion.cpp:1127 - prompt after extract and remove lora: "a lovely cat holding a sign says 'flux.cpp'"
stable-diffusion.cpp:655 - Attempting to apply 0 LoRAs
stable-diffusion.cpp:1132 - apply_loras completed, taking 0.00s
conditioner.hpp:1036 - parse 'a lovely cat holding a sign says 'flux.cpp'' to [['a lovely cat holding a sign says 'flux.cpp'', 1], ]
clip.hpp:311 - token length: 77
t5.hpp:397 - token length: 256
ggml_extend.hpp:1001 - t5 compute buffer size: 68.25 MB(RAM)
conditioner.hpp:1155 - computing condition graph completed, taking 13250 ms
conditioner.hpp:1036 - parse '' to [['', 1], ]
clip.hpp:311 - token length: 77
t5.hpp:397 - token length: 256
ggml_extend.hpp:1001 - t5 compute buffer size: 68.25 MB(RAM)
conditioner.hpp:1155 - computing condition graph completed, taking 13235 ms
stable-diffusion.cpp:1256 - get_learned_condition completed, taking 26490 ms
stable-diffusion.cpp:1279 - sampling using Euler method
stable-diffusion.cpp:1283 - generating image: 1/1 - seed 42
ggml_extend.hpp:1001 - flux compute buffer size: 398.50 MB(VRAM)
|==================================================| 20/20 - 1.40s/it
stable-diffusion.cpp:1315 - sampling completed, taking 38.94s
stable-diffusion.cpp:1323 - generating 1 latent images completed, taking 38.94s
stable-diffusion.cpp:1326 - decoding 1 latents
ggml_extend.hpp:1001 - vae compute buffer size: 1664.00 MB(VRAM)
stable-diffusion.cpp:987 - computing vae [mode: DECODE] graph completed, taking 1.44s
stable-diffusion.cpp:1336 - latent 1 decoded, taking 1.44s
stable-diffusion.cpp:1340 - decode_first_stage completed, taking 1.44s
stable-diffusion.cpp:1449 - txt2img completed in 66.88sWhich means that everything works as it should. Why doesn't it work in my project? This is strange. Although I ran test.py through the project's venv
(venv) PS C:\Coding\stable-diffusion.cpp\build> ./bin/release/sd --diffusion-model models/flux1-dev-Q6_K.gguf --clip_l models/clip_l.safetensors --t5xxl models/t5xxl_fp16.safetensors --vae models/ae.safetensors --cfg-scale 4 -H 768 -W 768 --steps 20 -p "a lovely cat holding a sign says 'flux.cpp'"
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes
[INFO ] stable-diffusion.cpp:202 - loading clip_l from 'models/clip_l.safetensors'
[WARN ] model.cpp:799 - unknown format models/clip_l.safetensors
[WARN ] stable-diffusion.cpp:204 - loading clip_l from 'models/clip_l.safetensors' failed
[INFO ] stable-diffusion.cpp:209 - loading t5xxl from 'models/t5xxl_fp16.safetensors'
[WARN ] model.cpp:799 - unknown format models/t5xxl_fp16.safetensors
[WARN ] stable-diffusion.cpp:211 - loading t5xxl from 'models/t5xxl_fp16.safetensors' failed
[INFO ] stable-diffusion.cpp:216 - loading diffusion model from 'models/flux1-dev-Q6_K.gguf'
[WARN ] model.cpp:799 - unknown format models/flux1-dev-Q6_K.gguf
[WARN ] stable-diffusion.cpp:218 - loading diffusion model from 'models/flux1-dev-Q6_K.gguf' failed
[INFO ] stable-diffusion.cpp:223 - loading vae from 'models/ae.safetensors'
[WARN ] model.cpp:799 - unknown format models/ae.safetensors
[WARN ] stable-diffusion.cpp:225 - loading vae from 'models/ae.safetensors' failed
[ERROR] stable-diffusion.cpp:231 - get sd version from file failed: ''
new_sd_ctx_t failed
In general, I will still try to see what is wrong from my side . Because if you set a strict argumentation, everything works, but if through the settings in the gradio interface or from ./bin/release/sd, an error occurs. In any case, thank you very much for your help.
This cat from test.py:
Dartvauder
commented
1 month ago Unfortunately, I cant seem to replicate the error. Are you on Linux or Mac? Could you run
nvcc --versionand send me what is returned? Do you also encounter the error when running a simple implementation of the code with the arguments hardcoded. For example, running the following file usingpython test.py:# test.py from stable_diffusion_cpp import StableDiffusion stable_diffusion = StableDiffusion( diffusion_model_path="inputs/image/quantize-flux/flux1-dev-Q6_K.gguf", clip_l_path="inputs/image/quantize-flux/clip_l.safetensors", t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors", vae_path="inputs/image/quantize-flux/ae.safetensors", ) output = stable_diffusion.txt_to_img( prompt="a lovely cat holding a sign says 'flux.cpp'", cfg_scale=1, sample_steps=4, sample_method="euler", ) output[0].save("output.png")My suggestion would be to build stable-diffusion.cpp directly (specifically building for CUBLAS), then try to generate FLUX images using the same model weights and arguments but with the stable-diffusion.cpp CLI. That way you can take advantage of extra documentation and previous user issues in the stable-diffusion.cpp repo. It may help narrow down the issue to something specific such as a missing argument in
CMAKE_ARGS. If you manage to build stable-diffusion.cpp for CUBLAS and can generate images without any errors, the problem is likely in my implementation of the Python bindings. Let me know how you get on.I am using Windows 11 64bit and this is what I got:
- (venv) PS C:\Coding\Python\NeuroSandboxWebUI> nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2024 NVIDIA Corporation Built on Thu_Mar_28_02:30:10_Pacific_Daylight_Time_2024 Cuda compilation tools, release 12.4, V12.4.131 Build cuda_12.4.r12.4/compiler.34097967_0
- I made a test.py file for these lines:
from stable_diffusion_cpp import StableDiffusion stable_diffusion = StableDiffusion( diffusion_model_path="inputs/image/quantize-flux/flux1-dev-Q6_K.gguf", clip_l_path="inputs/image/quantize-flux/clip_l.safetensors", t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors", vae_path="inputs/image/quantize-flux/ae.safetensors", ) output = stable_diffusion.txt_to_img( prompt="a lovely cat holding a sign says 'flux.cpp'", cfg_scale=4, sample_steps=20, sample_method="euler", ) output[0].save("output.png")ran it and got this:
stable-diffusion.cpp:157 - Using CUDA backend ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes stable-diffusion.cpp:202 - loading clip_l from 'inputs/image/quantize-flux/clip_l.safetensors' model.cpp:793 - load inputs/image/quantize-flux/clip_l.safetensors using safetensors format model.cpp:861 - init from 'inputs/image/quantize-flux/clip_l.safetensors' stable-diffusion.cpp:209 - loading t5xxl from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors' model.cpp:793 - load inputs/image/quantize-flux/t5xxl_fp16.safetensors using safetensors format model.cpp:861 - init from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors' stable-diffusion.cpp:216 - loading diffusion model from 'inputs/image/quantize-flux/flux1-dev-Q6_K.gguf' model.cpp:790 - load inputs/image/quantize-flux/flux1-dev-Q6_K.gguf using gguf format model.cpp:807 - init from 'inputs/image/quantize-flux/flux1-dev-Q6_K.gguf' stable-diffusion.cpp:223 - loading vae from 'inputs/image/quantize-flux/ae.safetensors' model.cpp:793 - load inputs/image/quantize-flux/ae.safetensors using safetensors format model.cpp:861 - init from 'inputs/image/quantize-flux/ae.safetensors' stable-diffusion.cpp:235 - Version: Flux Dev stable-diffusion.cpp:266 - Weight type: f16 stable-diffusion.cpp:267 - Conditioner weight type: f16 stable-diffusion.cpp:268 - Diffusion model weight type: q6_K stable-diffusion.cpp:269 - VAE weight type: f32 stable-diffusion.cpp:271 - ggml tensor size = 400 bytes stable-diffusion.cpp:310 - set clip_on_cpu to true stable-diffusion.cpp:313 - CLIP: Using CPU backend clip.hpp:171 - vocab size: 49408 clip.hpp:182 - trigger word img already in vocab ggml_extend.hpp:1050 - clip params backend buffer size = 235.06 MB(RAM) (196 tensors) ggml_extend.hpp:1050 - t5 params backend buffer size = 9083.77 MB(RAM) (219 tensors) ggml_extend.hpp:1050 - flux params backend buffer size = 9320.56 MB(VRAM) (780 tensors) ggml_extend.hpp:1050 - vae params backend buffer size = 160.00 MB(VRAM) (244 tensors) stable-diffusion.cpp:398 - loading weights model.cpp:1530 - loading tensors from inputs/image/quantize-flux/clip_l.safetensors model.cpp:1530 - loading tensors from inputs/image/quantize-flux/t5xxl_fp16.safetensors model.cpp:1685 - unknown tensor 'text_encoders.t5xxl.encoder.embed_tokens.weight | f16 | 2 [4096, 32128, 1, 1, 1]' in model file model.cpp:1530 - loading tensors from inputs/image/quantize-flux/flux1-dev-Q6_K.gguf model.cpp:1530 - loading tensors from inputs/image/quantize-flux/ae.safetensors stable-diffusion.cpp:497 - total params memory size = 18799.39MB (VRAM 9480.55MB, RAM 9318.83MB): clip 9318.83MB(RAM), unet 9320.56MB(VRAM), vae 160.00MB(VRAM), controlnet 0.00MB(VRAM), pmid 0.00MB(RAM) stable-diffusion.cpp:501 - loading model from '' completed, taking 39.93s stable-diffusion.cpp:518 - running in Flux FLOW mode stable-diffusion.cpp:572 - finished loaded file stable-diffusion.cpp:1378 - txt2img 512x512 stable-diffusion.cpp:1127 - prompt after extract and remove lora: "a lovely cat holding a sign says 'flux.cpp'" stable-diffusion.cpp:655 - Attempting to apply 0 LoRAs stable-diffusion.cpp:1132 - apply_loras completed, taking 0.00s conditioner.hpp:1036 - parse 'a lovely cat holding a sign says 'flux.cpp'' to [['a lovely cat holding a sign says 'flux.cpp'', 1], ] clip.hpp:311 - token length: 77 t5.hpp:397 - token length: 256 ggml_extend.hpp:1001 - t5 compute buffer size: 68.25 MB(RAM) conditioner.hpp:1155 - computing condition graph completed, taking 13250 ms conditioner.hpp:1036 - parse '' to [['', 1], ] clip.hpp:311 - token length: 77 t5.hpp:397 - token length: 256 ggml_extend.hpp:1001 - t5 compute buffer size: 68.25 MB(RAM) conditioner.hpp:1155 - computing condition graph completed, taking 13235 ms stable-diffusion.cpp:1256 - get_learned_condition completed, taking 26490 ms stable-diffusion.cpp:1279 - sampling using Euler method stable-diffusion.cpp:1283 - generating image: 1/1 - seed 42 ggml_extend.hpp:1001 - flux compute buffer size: 398.50 MB(VRAM) |==================================================| 20/20 - 1.40s/it stable-diffusion.cpp:1315 - sampling completed, taking 38.94s stable-diffusion.cpp:1323 - generating 1 latent images completed, taking 38.94s stable-diffusion.cpp:1326 - decoding 1 latents ggml_extend.hpp:1001 - vae compute buffer size: 1664.00 MB(VRAM) stable-diffusion.cpp:987 - computing vae [mode: DECODE] graph completed, taking 1.44s stable-diffusion.cpp:1336 - latent 1 decoded, taking 1.44s stable-diffusion.cpp:1340 - decode_first_stage completed, taking 1.44s stable-diffusion.cpp:1449 - txt2img completed in 66.88sWhich means that everything works as it should. Why doesn't it work in my project? This is strange. Although I ran test.py through the project's venv
- I was able to build stable-diffusion.cpp Using CUBLAS and running the generation via ../bin/release/sd --diffusion-model models/flux1-dev-Q6_K.gguf --clip_l models/clip_l.safetensors --t5xxl models/t5xxl_fp16.safetensors --vae models/ae.safetensors --cfg-scale 4 -H 768 -W 768 --steps 20 -p "a lovely cat holding a sign says 'flux.cpp'" and got this:
(venv) PS C:\Coding\stable-diffusion.cpp\build> ./bin/release/sd --diffusion-model models/flux1-dev-Q6_K.gguf --clip_l models/clip_l.safetensors --t5xxl models/t5xxl_fp16.safetensors --vae models/ae.safetensors --cfg-scale 4 -H 768 -W 768 --steps 20 -p "a lovely cat holding a sign says 'flux.cpp'" ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes [INFO ] stable-diffusion.cpp:202 - loading clip_l from 'models/clip_l.safetensors' [WARN ] model.cpp:799 - unknown format models/clip_l.safetensors [WARN ] stable-diffusion.cpp:204 - loading clip_l from 'models/clip_l.safetensors' failed [INFO ] stable-diffusion.cpp:209 - loading t5xxl from 'models/t5xxl_fp16.safetensors' [WARN ] model.cpp:799 - unknown format models/t5xxl_fp16.safetensors [WARN ] stable-diffusion.cpp:211 - loading t5xxl from 'models/t5xxl_fp16.safetensors' failed [INFO ] stable-diffusion.cpp:216 - loading diffusion model from 'models/flux1-dev-Q6_K.gguf' [WARN ] model.cpp:799 - unknown format models/flux1-dev-Q6_K.gguf [WARN ] stable-diffusion.cpp:218 - loading diffusion model from 'models/flux1-dev-Q6_K.gguf' failed [INFO ] stable-diffusion.cpp:223 - loading vae from 'models/ae.safetensors' [WARN ] model.cpp:799 - unknown format models/ae.safetensors [WARN ] stable-diffusion.cpp:225 - loading vae from 'models/ae.safetensors' failed [ERROR] stable-diffusion.cpp:231 - get sd version from file failed: '' new_sd_ctx_t failedIn general, I will still try to see what is wrong from my side . Because if you set a strict argumentation, everything works, but if through the settings in the gradio interface or from ./bin/release/sd, an error occurs. In any case, thank you very much for your help.
This cat from test.py:
I even tried this hard method in my main part of the app
if enable_quantize:
stable_diffusion = StableDiffusion(
diffusion_model_path="inputs/image/quantize-flux/flux1-dev-Q6_K.gguf",
clip_l_path="inputs/image/quantize-flux/clip_l.safetensors",
t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors",
vae_path="inputs/image/quantize-flux/ae.safetensors",
wtype="default")
output = stable_diffusion.txt_to_img(
prompt="a lovely cat holding a sign says 'flux.cpp'",
cfg_scale=4,
sample_steps=20,
sample_method="euler",
)and still get this error
stable-diffusion.cpp:157 - Using CUDA backend
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes
stable-diffusion.cpp:202 - loading clip_l from 'inputs/image/quantize-flux/clip_l.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/clip_l.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/clip_l.safetensors'
stable-diffusion.cpp:209 - loading t5xxl from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/t5xxl_fp16.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
stable-diffusion.cpp:216 - loading diffusion model from 'inputs/image/quantize-flux/flux1-dev-Q6_K.gguf'
model.cpp:790 - load inputs/image/quantize-flux/flux1-dev-Q6_K.gguf using gguf format
model.cpp:807 - init from 'inputs/image/quantize-flux/flux1-dev-Q6_K.gguf'
stable-diffusion.cpp:223 - loading vae from 'inputs/image/quantize-flux/ae.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/ae.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/ae.safetensors'
stable-diffusion.cpp:235 - Version: Flux Dev
stable-diffusion.cpp:266 - Weight type: f16
stable-diffusion.cpp:267 - Conditioner weight type: f16
stable-diffusion.cpp:268 - Diffusion model weight type: q6_K
stable-diffusion.cpp:269 - VAE weight type: f32
stable-diffusion.cpp:271 - ggml tensor size = 400 bytes
stable-diffusion.cpp:310 - set clip_on_cpu to true
stable-diffusion.cpp:313 - CLIP: Using CPU backend
clip.hpp:171 - vocab size: 49408
clip.hpp:182 - trigger word img already in vocab
ggml_extend.hpp:1050 - clip params backend buffer size = 235.06 MB(RAM) (196 tensors)
ggml_extend.hpp:1050 - t5 params backend buffer size = 9083.77 MB(RAM) (219 tensors)
Traceback (most recent call last):
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\queueing.py", line 536, in process_events
response = await route_utils.call_process_api(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\route_utils.py", line 321, in call_process_api
output = await app.get_blocks().process_api(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1935, in process_api
result = await self.call_function(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1520, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2144, in run_sync_in_worker_thread
return await future
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
result = context.run(func, *args)
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\utils.py", line 826, in wrapper
response = f(*args, **kwargs)
File "C:\Coding\Python\NeuroSandboxWebUI\LaunchFiles\appEN.py", line 4118, in generate_image_flux
stable_diffusion = StableDiffusion(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\stable_diffusion_cpp\stable_diffusion.py", line 122, in __init__
self._model = _StableDiffusionModel(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\stable_diffusion_cpp\_internals.py", line 79, in __init__
self.model = sd_cpp.new_sd_ctx(
OSError: exception: access violation reading 0x0000000000000000In general, most likely the error is on my side and I have to find it. Thanks again for your help. I think there is nothing to fix on your side anymore, because Test.py showed that everything works fine.
william-murray1204
commented
1 month ago No problem at all, happy to help.
Just quickly, could you print and send all of the arguments that are generated in your code and passed into the StableDiffusion() and stable_diffusion.txt_to_img() functions. It’s possible an invalid argument is being generated somewhere in your code (such as an invalid path or a cfg_scale that is too big, etc) and i have not handled it correctly so its printing this ambiguous error message.
william-murray1204
commented
1 month ago Its also possible this is a VRAM issue / unhandled “out of memory” error. Does your code load other things / models into memory which might be causing issues. If you watch task manager, does it look like your GPU is maxing out its memory?
Dartvauder
commented
1 month ago No problem at all, happy to help.
Just quickly, could you print and send all of the arguments that are generated in your code and passed into the StableDiffusion() and stable_diffusion.txt_to_img() functions. It’s possible an invalid argument is being generated somewhere in your code (such as an invalid path or a cfg_scale that is too big, etc) and i have not handled it correctly so its printing this ambiguous error message.
I have an application with many models and interfaces for them. I can send you the full codes that are responsible only for flux generation
Def function for generation:
def generate_image_flux(prompt, model_name, quantize_model_name, enable_quantize, seed, lora_model_names, lora_scales, guidance_scale, height, width, num_inference_steps, max_sequence_length, output_format="png"):
device = "cuda" if torch.cuda.is_available() else "cpu"
if seed == "" or seed is None:
seed = random.randint(0, 2 ** 32 - 1)
else:
seed = int(seed)
generator = torch.Generator(device).manual_seed(seed)
flux_model_path = os.path.join("inputs", "image", "flux", model_name)
try:
if enable_quantize:
quantize_flux_model_path = os.path.join("inputs", "image", "quantize-flux", f"{quantize_model_name}.gguf")
lora_model_path = os.path.join("inputs", "image", "flux-lora", f"{lora_model_names}.safetensors")
if not quantize_model_name:
return None, "Please select a quantize Flux model!"
stable_diffusion = StableDiffusion(
diffusion_model_path=quantize_flux_model_path,
clip_l_path="inputs/image/quantize-flux/clip_l.safetensors",
t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors",
vae_path="inputs/image/quantize-flux/ae.safetensors",
lora_model_dir=lora_model_path,
wtype="default")
output = stable_diffusion.txt_to_img(
prompt=prompt,
cfg_scale=guidance_scale,
height=height,
width=width,
sample_steps=num_inference_steps,
seed=seed,
sample_method="euler")
else:
if not os.path.exists(flux_model_path):
print(f"Downloading Flux {model_name} model...")
os.makedirs(flux_model_path, exist_ok=True)
Repo.clone_from(f"https://huggingface.co/black-forest-labs/{model_name}", flux_model_path)
print(f"Flux {model_name} model downloaded")
pipe = FluxPipeline.from_pretrained(flux_model_path, torch_dtype=torch.bfloat16)
pipe.to(device)
pipe.enable_model_cpu_offload()
pipe.enable_sequential_cpu_offload()
pipe.vae.enable_slicing()
pipe.vae.enable_tiling()
pipe.to(torch.float16)
if isinstance(lora_scales, str):
lora_scales = [float(scale.strip()) for scale in lora_scales.split(',') if scale.strip()]
elif isinstance(lora_scales, (int, float)):
lora_scales = [float(lora_scales)]
lora_loaded = False
if lora_model_names and lora_scales:
if len(lora_model_names) != len(lora_scales):
print(
f"Warning: Number of LoRA models ({len(lora_model_names)}) does not match number of scales ({len(lora_scales)}). Using available scales.")
for i, lora_model_name in enumerate(lora_model_names):
if i < len(lora_scales):
lora_scale = lora_scales[i]
else:
lora_scale = 1.0
lora_model_path = os.path.join("inputs", "image", "flux-lora", lora_model_name)
if os.path.exists(lora_model_path):
adapter_name = os.path.splitext(os.path.basename(lora_model_name))[0]
try:
pipe.load_lora_weights(lora_model_path, adapter_name=adapter_name)
pipe.fuse_lora(lora_scale=lora_scale)
lora_loaded = True
print(f"Loaded LoRA {lora_model_name} with scale {lora_scale}")
except Exception as e:
print(f"Error loading LoRA {lora_model_name}: {str(e)}")
output = pipe(
prompt=prompt,
guidance_scale=guidance_scale,
height=height,
width=width,
num_inference_steps=num_inference_steps,
max_sequence_length=max_sequence_length,
generator=generator
).images[0]
today = datetime.now().date()
image_dir = os.path.join('outputs', f"Flux_{today.strftime('%Y%m%d')}")
os.makedirs(image_dir, exist_ok=True)
image_filename = f"flux_{datetime.now().strftime('%Y%m%d_%H%M%S')}.{output_format}"
image_path = os.path.join(image_dir, image_filename)
output.save(image_path, format=output_format.upper())
return image_path, f"Image generated successfully. Seed used: {seed}"
except Exception as e:
return None, str(e)
finally:
if enable_quantize:
del stable_diffusion
else:
del pipe
flush()Function for models lists in interface:
quantized_flux_models_list = [None] + [model.replace(".gguf", "") for model in os.listdir("inputs/image/quantize-flux") if
model.endswith(".gguf") or not model.endswith(".txt") and not model.endswith(".safetensors")]
flux_lora_models_list = [None] + [model for model in os.listdir("inputs/image/flux-lora") if
model.endswith(".safetensors")]Interface:
flux_interface = gr.Interface(
fn=generate_image_flux,
inputs=[
gr.Textbox(label="Enter your prompt"),
gr.Dropdown(choices=["FLUX.1-schnell", "FLUX.1-dev"], label="Select Flux model", value="FLUX.1-schnell"),
gr.Dropdown(choices=quantized_flux_models_list, label="Select quantized Flux model (optional if enabled quantize)", value=None),
gr.Checkbox(label="Enable Quantize", value=False),
gr.Textbox(label="Seed (optional)", value="")
],
additional_inputs=[
gr.Dropdown(choices=flux_lora_models_list, label="Select LORA models (optional)", value=None, multiselect=True),
gr.Textbox(label="LoRA Scales"),
gr.Slider(minimum=0.0, maximum=10.0, value=0.0, step=0.1, label="Guidance Scale"),
gr.Slider(minimum=256, maximum=2048, value=768, step=64, label="Height"),
gr.Slider(minimum=256, maximum=2048, value=1024, step=64, label="Width"),
gr.Slider(minimum=1, maximum=100, value=10, step=1, label="Steps"),
gr.Slider(minimum=1, maximum=1024, value=256, step=1, label="Max Sequence Length"),
gr.Radio(choices=["png", "jpeg"], label="Select output format", value="png", interactive=True)
],
additional_inputs_accordion=gr.Accordion(label="Flux Settings", open=False),
outputs=[
gr.Image(type="filepath", label="Generated image"),
gr.Textbox(label="Message", type="text")
],
title="NeuroSandboxWebUI - Flux",
description="This user interface allows you to generate images using Flux models. "
"You can select between Schnell and Dev models, and customize the generation settings. "
"Try it and see what happens!",
allow_flagging="never",
clear_btn=None,
stop_btn="Stop",
submit_btn="Generate"
)s also possible this is a VRAM issue / unhandled “out of memory” error. Does your code load other things / models into memory which might be causing issues. If you watch task manager, does it look like your GPU is maxing out its memory?
No, I optimized the application as much as I could (or know). The VRAM and RAM are not loaded and even when loading models into them, after finishing everything is unloaded using:
def flush():
gc.collect()
torch.cuda.empty_cache()and
finally:
if enable_quantize:
del stable_diffusion
else:
del pipe
flush()Interesting. I will have to have a better look at your code tomorrow to see if i can reproduce the error.
For now, your best bet might be a process of elimination to see if temporarily removing or hardcoding things fixes the issue.
Dartvauder
commented
1 month ago Interesting. I will have to have a better look at your code tomorrow to see if i can reproduce the error.
For now, your best bet might be a process of elimination to see if temporarily removing or hardcoding things fixes the issue.
I also tried to create a separate file where there is only the code for generating flux and its interface:
import gradio as gr
import torch
from stable_diffusion_cpp import StableDiffusion
import os
import random
from datetime import datetime
def generate_image_flux(prompt, negative_prompt, model_name, quantize_model_name, enable_quantize, seed, guidance_scale,
num_inference_steps, output_format="png"):
if seed == "" or seed is None:
seed = random.randint(0, 2 ** 32 - 1)
else:
seed = int(seed)
device = "cuda" if torch.cuda.is_available() else "cpu"
torch.manual_seed(seed)
try:
if enable_quantize:
quantize_flux_model_path = os.path.join("inputs", "image", "quantize-flux", f"{quantize_model_name}.gguf")
if not quantize_model_name:
return None, "Please select a quantize Flux model!"
stable_diffusion = StableDiffusion(
diffusion_model_path=quantize_flux_model_path,
clip_l_path="inputs/image/quantize-flux/clip_l.safetensors",
t5xxl_path="inputs/image/quantize-flux/t5xxl_fp16.safetensors",
vae_path="inputs/image/quantize-flux/ae.safetensors",
wtype="default")
output = stable_diffusion.txt_to_img(
prompt=prompt,
negative_prompt=negative_prompt,
cfg_scale=guidance_scale,
sample_steps=num_inference_steps,
seed=seed,
sample_method="euler")
else:
return None, "This test is for quantized model only. Please enable quantization."
today = datetime.now().date()
image_dir = os.path.join('outputs', f"Flux_{today.strftime('%Y%m%d')}")
os.makedirs(image_dir, exist_ok=True)
image_filename = f"flux_{datetime.now().strftime('%Y%m%d_%H%M%S')}.{output_format}"
image_path = os.path.join(image_dir, image_filename)
output[0].save(image_path, format=output_format.upper())
return image_path, f"Image generated successfully. Seed used: {seed}"
except Exception as e:
return None, str(e)
finally:
if 'stable_diffusion' in locals():
del stable_diffusion
torch.cuda.empty_cache()
quantized_flux_models_list = [None] + [model.replace(".gguf", "") for model in os.listdir("inputs/image/quantize-flux") if
model.endswith(".gguf") or not model.endswith(".txt") and not model.endswith(".safetensors")]
iface = gr.Interface(
fn=generate_image_flux,
inputs=[
gr.Textbox(label="Enter your prompt"),
gr.Textbox(label="Enter your negative prompt", value=""),
gr.Textbox(label="Model name (not used in this test)", value=""),
gr.Dropdown(choices=quantized_flux_models_list, label="Select quantized Flux model", value=None),
gr.Checkbox(label="Enable Quantize", value=True),
gr.Textbox(label="Seed (optional)", value=""),
gr.Slider(minimum=1.0, maximum=20.0, value=7.5, step=0.1, label="Guidance Scale"),
gr.Slider(minimum=1, maximum=100, value=30, step=1, label="Inference Steps"),
gr.Radio(choices=["png", "jpeg"], label="Select output format", value="png", interactive=True)
],
outputs=[
gr.Image(type="filepath", label="Generated image"),
gr.Textbox(label="Message", type="text")
],
title="Flux Quantized Model Test",
description="This is a test interface for the Flux quantized model.",
)
iface.launch()But in the end I get the same error:
stable-diffusion.cpp:157 - Using CUDA backend
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes
stable-diffusion.cpp:202 - loading clip_l from 'inputs/image/quantize-flux/clip_l.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/clip_l.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/clip_l.safetensors'
stable-diffusion.cpp:209 - loading t5xxl from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/t5xxl_fp16.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/t5xxl_fp16.safetensors'
stable-diffusion.cpp:216 - loading diffusion model from 'inputs/image/quantize-flux/flux1-dev-Q6_K.gguf'
model.cpp:790 - load inputs/image/quantize-flux/flux1-dev-Q6_K.gguf using gguf format
model.cpp:807 - init from 'inputs/image/quantize-flux/flux1-dev-Q6_K.gguf'
stable-diffusion.cpp:223 - loading vae from 'inputs/image/quantize-flux/ae.safetensors'
model.cpp:793 - load inputs/image/quantize-flux/ae.safetensors using safetensors format
model.cpp:861 - init from 'inputs/image/quantize-flux/ae.safetensors'
stable-diffusion.cpp:235 - Version: Flux Dev
stable-diffusion.cpp:266 - Weight type: f16
stable-diffusion.cpp:267 - Conditioner weight type: f16
stable-diffusion.cpp:268 - Diffusion model weight type: q6_K
stable-diffusion.cpp:269 - VAE weight type: f32
stable-diffusion.cpp:271 - ggml tensor size = 400 bytes
stable-diffusion.cpp:310 - set clip_on_cpu to true
stable-diffusion.cpp:313 - CLIP: Using CPU backend
clip.hpp:171 - vocab size: 49408
clip.hpp:182 - trigger word img already in vocab
ggml_extend.hpp:1050 - clip params backend buffer size = 235.06 MB(RAM) (196 tensors)
ggml_extend.hpp:1050 - t5 params backend buffer size = 9083.77 MB(RAM) (219 tensors)
Traceback (most recent call last):
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\queueing.py", line 536, in process_events
response = await route_utils.call_process_api(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\route_utils.py", line 321, in call_process_api
output = await app.get_blocks().process_api(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1935, in process_api
result = await self.call_function(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\blocks.py", line 1520, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2144, in run_sync_in_worker_thread
return await future
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
result = context.run(func, *args)
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\gradio\utils.py", line 826, in wrapper
response = f(*args, **kwargs)
File "C:\Coding\Python\NeuroSandboxWebUI\LaunchFiles\appEN.py", line 4118, in generate_image_flux
stable_diffusion = StableDiffusion(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\stable_diffusion_cpp\stable_diffusion.py", line 122, in __init__
self._model = _StableDiffusionModel(
File "C:\Coding\Python\NeuroSandboxWebUI\venv\lib\site-packages\stable_diffusion_cpp\_internals.py", line 79, in __init__
self.model = sd_cpp.new_sd_ctx(
OSError: exception: access violation reading 0x0000000000000000It seems to me that the problem is due to the gradio library. Because how else can you explain that if you just run the generation without passing it to the interface, everything works fine
Dartvauder
commented
1 month ago Good evening. I want to inform you (if you are interested), I finally got it all done. You were right, heavy coding helped. I made a separate script for working with quantized models, which is launched through the main code.
Main code:
if enable_quantize:
params = {
'prompt': prompt,
'guidance_scale': guidance_scale,
'height': height,
'width': width,
'num_inference_steps': num_inference_steps,
'seed': seed,
'quantize_flux_model_path': f"{quantize_model_name}"
}
env = os.environ.copy()
env['PYTHONPATH'] = os.pathsep.join(sys.path)
result = subprocess.run([sys.executable, 'inputs/image/quantize-flux/flux-quantize.py', json.dumps(params)],
capture_output=True, text=True)
if result.returncode != 0:
return None, f"Error in flux-quantize.py: {result.stderr}"
image_path = None
for line in result.stdout.split('\n'):
if line.startswith("IMAGE_PATH:"):
image_path = line.split("IMAGE_PATH:")[1].strip()
break
if not image_path:
return None, "Image path not found in the output"
if not os.path.exists(image_path):
return None, f"Generated image not found at {image_path}"
return image_path, f"Image generated successfully. Seed used: {seed}"and script:
import sys
import json
from stable_diffusion_cpp import StableDiffusion
import os
from datetime import datetime
def generate_image(params):
model_dir = os.path.dirname(os.path.abspath(__file__))
diffusion_model_path = os.path.join(model_dir, params.get('quantize_flux_model_path'))
clip_l_path = os.path.join(model_dir, "clip_l.safetensors")
t5xxl_path = os.path.join(model_dir, "t5xxl_fp16.safetensors")
vae_path = os.path.join(model_dir, "ae.safetensors")
stable_diffusion = StableDiffusion(
diffusion_model_path=diffusion_model_path,
clip_l_path=clip_l_path,
t5xxl_path=t5xxl_path,
vae_path=vae_path,
wtype="default"
)
output = stable_diffusion.txt_to_img(
prompt=params['prompt'],
cfg_scale=params['guidance_scale'],
height=params['height'],
width=params['width'],
sample_steps=params['num_inference_steps'],
seed=params['seed'],
sample_method="euler"
)
output_dir = os.path.join('outputs', f"Flux_{datetime.now().strftime('%Y%m%d')}")
os.makedirs(output_dir, exist_ok=True)
image_filename = f"flux-quantize_{datetime.now().strftime('%Y%m%d_%H%M%S')}.png"
image_path = os.path.join(output_dir, image_filename)
output[0].save(image_path, format="PNG")
return image_path
if __name__ == "__main__":
try:
params = json.loads(sys.argv[1])
image_path = generate_image(params)
print(f"IMAGE_PATH:{image_path}")
except Exception as e:
print(f"Error occurred: {str(e)}", file=sys.stderr)
import traceback
traceback.print_exc(file=sys.stderr)
sys.exit(1)
Thanks for your code. Everything works great. Good luck in developing!
Good afternoon, is there an update planned for the FLUX models? I am doing my own project and would really like to integrate yours into mine to give people support for GGUF models for flux in gradio interface