Comments (3)
I used 10 pictures of a person's face to fine-tune the model, but the results don't seem to be as good as described in the README.md. Can you provide more details on how to train the model?
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Hi, thanks for your interest in this work.
You can find more detailed instructions for fine-tuning on faces in the issue here. These results are with regularization images obtained using clip-retrieval only.
Training on faces is better with fine-tuning all cross-attention parameters and requires longer training time with more images compared to other categories.
Hopefully, this should help in getting better results.
from custom-diffusion.
@nupurkmr9 ,Thank you for your prompt response and for sharing the detailed instructions for fine-tuning on faces. I appreciate your help.
I'm happy to inform you that I was able to deal with the issue. I followed your instructions and fine-tuned all cross-attention parameters, which required longer training time with more images compared to other categories, as you mentioned. The results are much better now, and I'm satisfied with the performance.
Thanks again for your support:)
from custom-diffusion.
Related Issues (20)
- About the train data and val data! HOT 1
- TypeError: ModelCheckpoint.__init__() got an unexpected keyword argument 'every_n_epochs' HOT 2
- License HOT 1
- Can I fine-tune it using other pre-trained model other than sd-v1-4.ckpt? HOT 1
- Moon Gate+ Evaluation q HOT 3
- Analysis of change in weights on updating all network weights during fine-tuning HOT 1
- 'Attention' object has no attribute 'cross_attention_norm' HOT 3
- How to train the model withot using the regularized dataset HOT 2
- How to Visualize Attention Maps to Analyze Compositions? HOT 2
- CustomConcept101 dataset HOT 3
- Plan for integration of SDXL? It seems to require more work than changing the MODEL_NAME HOT 6
- I have a bug with the diffusers HOT 1
- knn.laion.ai link error HOT 2
- KeyError in visualize attn maps HOT 4
- No module named 'diffusers.models.cross_attention' HOT 1
- Errors in using diffuser version HOT 3
- A question for the regularization captions HOT 1
- questions about crossattn in CustomDiffusionAttnProcessor
- Question about the cross attention HOT 1
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