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Kohya S
2023-01-29 21:23:05 +09:00
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@@ -6,6 +6,11 @@ __Stable Diffusion web UI now seems to support LoRA trained by ``sd-scripts``.__
Note: The LoRA models for SD 2.x is not supported too in Web UI.
- 29 Jan. 2023, 2023/1/29
- Add ``--lr_scheduler_num_cycles`` and ``--lr_scheduler_power`` options for ``train_network.py`` for cosine_with_restarts and polynomial learning rate schedulers.
- Fixed U-Net ``sample_size`` parameter to ``64`` when converting from SD to Diffusers format, in ``convert_diffusers20_original_sd.py``
- ``--lr_scheduler_num_cycles`` と ``--lr_scheduler_power`` オプションを ``train_network.py`` に追加しました。前者は cosine_with_restarts、後者は polynomial の学習率スケジューラに有効です。
- ``convert_diffusers20_original_sd.py`` で SD 形式から Diffusers に変換するときの U-Net の ``sample_size`` パラメータを ``64`` に修正しました。
- 26 Jan. 2023, 2023/1/26
- Add Textual Inversion training. Documentation is [here](./train_ti_README-ja.md) (in Japanese.)
- Textual Inversionの学習をサポートしました。ドキュメントは[こちら](./train_ti_README-ja.md)。