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author | XavierXiao <xiaozhisheng950@gmail.com> | 2022-09-06 09:41:12 -0700 |
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committer | XavierXiao <xiaozhisheng950@gmail.com> | 2022-09-06 09:41:12 -0700 |
commit | d5def4abd8cde2b5c3f6c53643fa53a27c175aa7 (patch) | |
tree | 416137660e3b189bef632dd7bb9c472423c3fea8 | |
parent | change config (diff) | |
parent | Update README.md (diff) |
Merge branch 'main' of github.com:XavierXiao/Dreambooth-Stable-Diffusion
-rw-r--r-- | README.md | 4 |
1 files changed, 4 insertions, 0 deletions
@@ -33,4 +33,8 @@ python main.py --base configs/stable-diffusion/v1-finetune_unfrozen.yaml --class_word <xxx> ``` +Detailed configuration can be found in ```configs/stable-diffusion/v1-finetune_unfrozen.yaml```. In particular, the default learning rate is ```1.0e-6``` as I found the ```1.0e-5``` in the Dreambooth paper leads to poor editability. The parameter ```reg_weight``` corresponds to the weight of regularization in the Dreambooth paper, and the default is set to ```1.0```. + +Dreambooth requires a placeholder word ```[V]```, called identifier, as in the paper. This identifier needs to be a relatively rare tokens in the vocabulary. The original paper approaches this by using a rare word in T5-XXL tokenizer. For simplicity, here I just use a random word ```sks``` and hard coded it.. If you want to change that, simply make a change in [this file](https://github.com/XavierXiao/Dreambooth-Stable-Diffusion/blob/main/ldm/data/personalized.py#L10). + ### Generation |