"Is there an XL version of extract_lora_from_models.py?"

C:\Users\86189>C:\Users\86189\Desktop\lora-scripts-main\venv\Scripts\python C:\Users\86189\Desktop\lora-scripts-main\sd-scripts\networks\extract_lora_from_models.py --v2 --model_org E:\sd-webui-aki-v4.7\models\Stable-diffusion\noobaiXLNAIXL_epsilonPred075.safetensors --model_tuned E:\sd-webui-aki-v4.7\models\Stable-diffusion\tPonynai3_v55.safetensors --saveto lora-C:\Users\86189\Desktop\000.safetensors --dim 4 2024-11-13 21:18:23 WARNING A matching Triton is not available, some optimizations will not be enabled init.py:59 Traceback (most recent call last): File "C:\Users\86189\Desktop\lora-scripts-main\venv\lib\site-packages\xformers_ init__.py", line 55, in _is_triton_available from xformers.triton.softmax import softmax as triton_softmax # noqa File "C:\Users\86189\Desktop\lora-scripts-main\venv\lib\site-packages\xformers\tr iton\softmax.py", line 11, in import triton ModuleNotFoundError: No module named 'triton' 2024-11-13 21:18:24 INFO loading original SD model : extract_lora_from_models.py:75 E:\sd-webui-aki-v4.7\models\Stable-diffusion\noobaiXLNAIXL_e psilonPred075.safetensors INFO UNet2DConditionModel: 64, [5, 10, 20, 20], 1024, True, False original_unet.py:1387 Traceback (most recent call last): File "C:\Users\86189\Desktop\lora-scripts-main\sd-scripts\networks\extract_lora_from_models.py", line 363, in svd(**vars(args)) File "C:\Users\86189\Desktop\lora-scripts-main\sd-scripts\networks\extract_lora_from_models.py", line 76, in svd text_encodero, , unet_o = model_util.load_models_from_stable_diffusion_checkpoint(v2, model_org) File "C:\Users\86189\Desktop\lora-scripts-main\sd-scripts\networks..\library\model_util.py", line 1008, in load_models_from_stable_diffusion_checkpoint info = unet.load_state_dict(converted_unet_checkpoint) File "C:\Users\86189\Desktop\lora-scripts-main\venv\lib\site-packages\torch\nn\modules\module.py", line 2153, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for UNet2DConditionModel: Missing key(s) in state_dict: "down_blocks.0.attentions.0.norm.weight", "down_blocks.0.attentions.0.norm.bias", "down_blocks.0.attentions.0.proj_in.weight", "down_blocks.0.attentions.0.proj_in.bias", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_q.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_k.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_v.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_out.0.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn1.to_out.0.bias", "down_blocks.0.attentions.0.transformer_blocks.0.ff.net.0.proj.weight", "down_blocks.0.attentions.0.transformer_blocks.0.ff.net.0.proj.bias", "down_blocks.0.attentions.0.transformer_blocks.0.ff.net.2.weight", "down_blocks.0.attentions.0.transformer_blocks.0.ff.net.2.bias", "down_blocks.0.attentions.0.transformer_blocks.0.attn2.to_q.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn2.to_k.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn2.to_v.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn2.to_out.0.weight", "down_blocks.0.attentions.0.transformer_blocks.0.attn2.to_out.0.bias", "down_blocks.0.attentions.0.transformer_blocks.0.norm1.weight", "down_blocks.0.attentions.0.transformer_blocks.0.norm1.bias", "down_blocks.0.attentions.0.transformer_blocks.0.norm2.weight", "down_blocks.0.attentions.0.transformer_blocks.0.norm2.bias", "down_blocks.0.attentions.0.transformer_blocks.0.norm3.weight", "down_blocks.0.attentions.0.transformer_blocks.0.norm3.bias", "down_blocks.0.attentions.0.proj_out.weight", "down_blocks.0.attentions.0.proj_out.bias", "down_blocks.0.attentions.1.norm.weight", "down_blocks.0.attentions.1.norm.bias", "down_blocks.0.attentions.1.proj_in.weight", "down_blocks.0.attentions.1.proj_in.bias", "down_blocks.0.attentions.1.transformer_blocks.0.attn1.to_q.weight", "down_blocks.0.attentions.1.transformer_blocks.0.attn1.to_k.weight", "down_blocks.0.attentions.1.transformer_blocks.0.attn1.to_v.weight", "down_blocks.0.attentions.1.transformer_blocks.0.attn1.to_out.0.weight", "down_blocks.0.attentions.1.transformer_blocks.0.attn1.to_out.0.bias", "down_blocks.0.attentions.1.transformer_blocks.0.ff.net.0.proj.weight", "down_blocks.0.attentions.1.transformer_blocks.0.ff.net.0.proj.bias", "down_blocks.0.attentions.1.transformer_blocks.0.ff.net.2.weight", "down_blocks.0.attentions.1.transformer_blocks.0.ff.net.2.bias", "down_blocks.0.attentions.1.transformer_blocks.0.attn2.to_q.weight", "down_blocks.0.attentions.1.transformer_blocks.0.attn2.to_k.weight", "down_blocks.0.attentions.1.transformer_blocks.0.attn2.to_v.weight", "down_blocks.0.attentions.1.transformer_blocks.0.attn2.to_out.0.weight", "down_blocks.0.attentions.1.transformer_blocks.0.attn2.to_out.0.bias", "down_blocks.0.attentions.1.transformer_blocks.0.norm1.weight", "down_blocks.0.attentions.1.transformer_blocks.0.norm1.bias", "down_blocks.0.attentions.1.transformer_blocks.0.norm2.weight", "down_blocks.0.attentions.1.transformer_blocks.0.norm2.bias", "down_blocks.0.attentions.1.transformer_blocks.0.norm3.weight", "down_blocks.0.attentions.1.transformer_blocks.0.norm3.bias", "down_blocks.0.attentions.1.proj_out.weight", "down_blocks.0.attentions.1.proj_out.bias", "down_blocks.2.downsamplers.0.conv.weight", "down_blocks.2.downsamplers.0.conv.bias", "down_blocks.3.resnets.0.norm1.weight", "down_blocks.3.resnets.0.norm1.bias", "down_blocks.3.resnets.0.conv1.weight", "down_blocks.3.resnets.0.conv1.bias", "down_blocks.3.resnets.0.time_emb_proj.weight", "down_blocks.3.resnets.0.time_emb_proj.bias", "down_blocks.3.resnets.0.norm2.weight", "down_blocks.3.resnets.0.norm2.bias", "down_blocks.3.resnets.0.conv2.weight", "down_blocks.3.resnets.0.conv2.bias", "down_blocks.3.resnets.1.norm1.weight", "down_blocks.3.resnets.1.norm1.bias", "down_blocks.3.resnets.1.conv1.weight", "down_blocks.3.resnets.1.conv1.bias", "down_blocks.3.resnets.1.time_emb_proj.weight", "down_blocks.3.resnets.1.time_emb_proj.bias", "down_blocks.3.resnets.1.norm2.weight", "down_blocks.3.resnets.1.norm2.bias", "down_blocks.3.resnets.1.conv2.weight", "down_blocks.3.resnets.1.conv2.bias", "up_blocks.2.attentions.0.norm.weight", "up_blocks.2.attentions.0.norm.bias", "up_blocks.2.attentions.0.proj_in.weight", "up_blocks.2.attentions.0.proj_in.bias", "up_blocks.2.attentions.0.transformer_blocks.0.attn1.to_q.weight", "up_blocks.2.attentions.0.transformer_blocks.0.attn1.to_k.weight", "up_blocks.2.attentions.0.transformer_blocks.0.attn1.to_v.weight", "up_blocks.2.attentions.0.transformer_blocks.0.attn1.to_out.0.weight", "up_blocks.2.attentions.0.transformer_blocks.0.attn1.to_out.0.bias", "up_blocks.2.attentions.0.transformer_blocks.0.ff.net.0.proj.weight", "up_blocks.2.attentions.0.transformer_blocks.0.ff.net.0.proj.bias", "up_blocks.2.attentions.0.transformer_blocks.0.ff.net.2.weight", "up_blocks.2.attentions.0.transformer_blocks.0.ff.net.2.bias", "up_blocks.2.attentions.0.transformer_blocks.0.attn2.to_q.weight", "up_blocks.2.attentions.0.transformer_blocks.0.attn2.to_k.weight", "up_blocks.2.attentions.0.transformer_blocks.0.attn2.to_v.weight", "up_blocks.2.attentions.0.transformer_blocks.0.attn2.to_out.0.weight", "up_blocks.2.attentions.0.transformer_blocks.0.attn2.to_out.0.bias", "up_blocks.2.attentions.0.transformer_blocks.0.norm1.weight",

--v2 error

kohya-ss / sd-scripts

"Is there an XL version of extract_lora_from_models.py?" #1781