error while trying to load dreambooth weights

[boradepecik]

I am trying to load dreambooth weights to try inference after finetuning sd with train_dreambooth_oft.py

I have tried both .load_lora_weights() and .unet_load_attn_procs(). both giving the same error:

Traceback (most recent call last): File "/home/depecikbora/oft/oft-db/fullimg.py", line 8, in pipe.load_lora_weights("hardmodel") File "/home/depecikbora/.pyenv/versions/3.10.6/lib/python3.10/site-packages/diffusers/loaders.py", line 928, in load_lora_weights self.load_lora_into_unet(state_dict, network_alphas=network_alphas, unet=self.unet) File "/home/depecikbora/.pyenv/versions/3.10.6/lib/python3.10/site-packages/diffusers/loaders.py", line 1210, in load_lora_into_unet unet.load_attn_procs(state_dict, network_alphas=network_alphas) File "/home/depecikbora/.pyenv/versions/3.10.6/lib/python3.10/site-packages/diffusers/loaders.py", line 479, in load_attn_procs raise ValueError( ValueError: None does not seem to be in the correct format expected by LoRA or Custom Diffusion training.

Here is the command i used to fine-tune the model: accelerate launch train_dreambooth_oft.py \ --pretrained_model_name_or_path="dreamlike-art/dreamlike-photoreal-2.0" \ --instance_data_dir="input9" \ --output_dir="hardmodel" \ --instance_prompt="a photo of sks t-shirt" \ --resolution=512 \ --train_batch_size=1 \ --gradient_accumulation_steps=1 \ --learning_rate=7e-4 \ --lr_scheduler="constant" \ --lr_warmup_steps=0 \ --max_train_steps=600 \ --seed="0" \ --eps=6e-5 \ --r="2" \ --coft

am i missing something here? or is there another way to do inference without using the diffusers library?

[lan-qing]

me too.