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Kohya S
2023-07-06 07:43:30 +09:00
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@@ -45,7 +45,7 @@ Summary of the feature:
- Use `--cache_text_encoder_outputs` option and caching latents.
- 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.
- `--network_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: