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update readme (#803)

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* update readme

* update readme

* fix typo
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Kohya S
2023-09-03 12:51:09 +09:00
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@@ -22,11 +22,21 @@ __Stable Diffusion web UI now seems to support LoRA trained by ``sd-scripts``.__
The feature of SDXL training is now available in sdxl branch as an experimental feature. The feature of SDXL training is now available in sdxl branch as an experimental feature.
Aug 13, 2023: The feature will be merged into the main branch soon. Following are the changes from the previous version. Sep 3, 2023: The feature will be merged into the main branch soon. Following are the changes from the previous version.
- ControlNet-LLLite is added. See [documentation](./docs/train_lllite_README.md) for details.
- JPEG XL is supported. [#786](https://github.com/kohya-ss/sd-scripts/pull/786)
- Peak memory usage is reduced. [#791](https://github.com/kohya-ss/sd-scripts/pull/791)
- Input perturbation noise is added. See [#798](https://github.com/kohya-ss/sd-scripts/pull/798) for details.
- Dataset subset now has `caption_prefix` and `caption_suffix` options. The strings are added to the beginning and the end of the captions before shuffling. You can specify the options in `.toml`.
- Other minor changes.
- Thanks for contributions from Isotr0py, vvern999, lansing and others!
Aug 13, 2023:
- LoRA-FA is added experimentally. Specify `--network_module networks.lora_fa` option instead of `--network_module networks.lora`. The trained model can be used as a normal LoRA model. - LoRA-FA is added experimentally. Specify `--network_module networks.lora_fa` option instead of `--network_module networks.lora`. The trained model can be used as a normal LoRA model.
Aug 12, 2023: Following are the changes from the previous version. Aug 12, 2023:
- The default value of noise offset when omitted has been changed to 0 from 0.0357. - The default value of noise offset when omitted has been changed to 0 from 0.0357.
- The different learning rates for each U-Net block are now supported. Specify with `--block_lr` option. Specify 23 values separated by commas like `--block_lr 1e-3,1e-3 ... 1e-3`. - The different learning rates for each U-Net block are now supported. Specify with `--block_lr` option. Specify 23 values separated by commas like `--block_lr 1e-3,1e-3 ... 1e-3`.