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Kohya S
2023-06-26 21:20:49 +09:00
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README.md
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@@ -30,6 +30,8 @@ Summary of the feature:
- `--cache_text_encoder_outputs`: Cache the outputs of the text encoders. This option is useful to reduce the GPU memory usage. This option cannot be used with options for shuffling or dropping the captions.
- `--no_half_vae`: Disable the half-precision (mixed-precision) VAE. VAE for SDXL seems to produce NaNs in some cases. This option is useful to avoid the NaNs.
`requirements.txt` is updated to support SDXL training.
### Tips for SDXL training
- The default resolution of SDXL is 1024x1024.
@@ -40,6 +42,7 @@ Summary of the feature:
- Use Adafactor optimizer. RMSprop 8bit or Adagrad 8bit may work. AdamW 8bit doesn't seem to work.
- The LoRA training can be done with 12GB GPU memory.
- `--train_unet_only` option is highly recommended for SDXL LoRA. Because SDXL has two text encoders, the result of the training will be unexpected.
- PyTorch 2 seems to use slightly less GPU memory than PyTorch 1.
Example of the optimizer settings for Adafactor with the fixed learning rate:
```
@@ -54,7 +57,7 @@ learning_rate = 4e-7 # SDXL original learning rate
These files do not contain requirements for PyTorch. Because the versions of them depend on your environment. Please install PyTorch at first (see installation guide below.)
The scripts are tested with PyTorch 1.12.1 and 1.13.0, Diffusers 0.10.2.
The scripts are tested with PyTorch 1.12.1 and 2.0.1, Diffusers 0.17.1.
## Links to how-to-use documents