fast-stable-diffusion
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Conversion error while Converting to Diffusers
Hey! I'm trying to do DreamBooth with the Deliberate v2.ckpt model from Hugging Face, but I get this conversion error when trying to convert to diffusers.
Is there a workaround you can do about this, or is this a Deliberate model issue?
Thank you!
Converting to Diffusers ...
Traceback (most recent call last):
File "/content/convertodiff.py", line 1130, in <module>
convert(args)
File "/content/convertodiff.py", line 1081, in convert
text_encoder, vae, unet = load_models_from_stable_diffusion_checkpoint(v2_model, args.model_to_load)
File "/content/convertodiff.py", line 846, in load_models_from_stable_diffusion_checkpoint
info = unet.load_state_dict(converted_unet_checkpoint)
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1671, 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: "up_blocks.0.upsamplers.0.conv.weight", "up_blocks.0.upsamplers.0.conv.bias", "up_blocks.1.upsamplers.0.conv.weight", "up_blocks.1.upsamplers.0.conv.bias", "up_blocks.2.upsamplers.0.conv.weight", "up_blocks.2.upsamplers.0.conv.bias".
Unexpected key(s) in state_dict: "up_blocks.0.attentions.2.conv.bias", "up_blocks.0.attentions.2.conv.weight".
rm: cannot remove '/content/stable-diffusion-custom': No such file or directory
Conversion error
Conversion error
---------------------------------------------------------------------------
KeyboardInterrupt Traceback (most recent call last)
<ipython-input-5-c3ccfb24c5ee> in <module>
226 while not os.path.exists('/content/stable-diffusion-custom/unet/diffusion_pytorch_model.bin'):
227 print('Conversion error')
--> 228 time.sleep(5)
229 else:
230 while os.path.getsize('/content/model.ckpt') < 1810671599:
KeyboardInterrupt:
I had the same problem for weeks
Pretty sure Dreambooth is busted right now, been getting errors all day.
Try putting XpucT/Deliberate
in path_to_huggingface instead.
100% same here when I put the model link instead of HF link, just wondering what's the conditions to meet when only loading a ckpt file, I know I can just train a lora model instead, but still wanna use the model training workflow.
There's a fork of Fast DB by TheOvercomer08 that can train all models, I've been using it successfully for some time now
https://github.com/theovercomer8/sd-playground
There's a fork of Fast DB by TheOvercomer08 that can train all models, I've been using it successfully for some time now
https://github.com/theovercomer8/sd-playground
Even that one has the ModuleNotFoundError Dreambooth is cooked atm