{"id":20844836,"url":"https://github.com/ai-dock/kohya_ss","last_synced_at":"2025-05-09T02:26:52.279Z","repository":{"id":242098327,"uuid":"808654120","full_name":"ai-dock/kohya_ss","owner":"ai-dock","description":"Kohya's GUI docker images for use in GPU cloud and local environments. 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You should use a [provisioning script](https://github.com/ai-dock/base-image/wiki/4.0-Running-the-Image#provisioning-script) to automatically configure your container. You can find examples in `config/provisioning`.\n\n## Documentation\n\nAll AI-Dock containers share a common base which is designed to make running on cloud services such as [vast.ai](https://link.ai-dock.org/vast.ai) as straightforward and user friendly as possible.\n\nCommon features and options are documented in the [base wiki](https://github.com/ai-dock/base-image/wiki) but any additional features unique to this image will be detailed below.\n\n\n#### Version Tags\n\nThe `:latest` tag points to `:latest-cuda`\n\nTags follow these patterns:\n\n##### _CUDA_\n- `:v2-cuda-[x.x.x]-base-[ubuntu-version]`\n\n- `:latest-cuda` \u0026rarr; `:v2-cuda-12.1.1-base-22.04`\n\n##### _ROCm_\n- `:v2-rocm-[x.x.x]-core-[ubuntu-version]`\n\n- `:latest-rocm` \u0026rarr; `:v2-rocm-6.0-core-22.04`\n\n\nBrowse [here](https://github.com/ai-dock/kohya_ss/pkgs/container/kohya_ss) for an image suitable for your target environment.\n\nSupported Python versions: `3.10`\n\nSupported Platforms: `NVIDIA CUDA`, `AMD ROCm`\n\n## Additional Environment Variables\n\n| Variable                 | Description |\n| ------------------------ | ----------- |\n| `AUTO_UPDATE`            | Update Kohya_ss on startup (default `false`) |\n| `KOHYA_ARGS`             | Startup arguments |\n| `KOHYA_PORT_HOST`        | Kohya's GUI port (default `7860`) |\n| `KOHYA_REF`              | Git reference for auto update. Accepts branch, tag or commit hash. Default: latest release |\n| `KOHYA_URL`              | Override `$DIRECT_ADDRESS:port` with URL for Kohya's GUI |\n| `TENSORBOARD_ARGS`       | Startup arguments (default `--logdir /opt/kohya_ss/logs`) |\n| `TENSORBOARD_PORT_HOST`  | Tensorboard port (default `6006`) |\n| `TENSORBOARD_URL`        | Override `$DIRECT_ADDRESS:port` with URL for Tensorboard |\n\nSee the base environment variables [here](https://github.com/ai-dock/base-image/wiki/2.0-Environment-Variables) for more configuration options.\n\n### Additional Python Environments\n\n| Environment    | Packages |\n| -------------- | ----------------------------------------- |\n| `kohya`        | Kohya's GUI and dependencies |\n\nThis virtualenv will be activated on shell login.\n\n~~See the base environments [here](https://github.com/ai-dock/base-image/wiki/1.0-Included-Software#installed-micromamba-environments).~~\n\n\n## Additional Services\n\nThe following services will be launched alongside the [default services](https://github.com/ai-dock/base-image/wiki/1.0-Included-Software) provided by the base image.\n\n### Kohya's GUI\n\nThe service will launch on port `7860` unless you have specified an override with `KOHYA_PORT`.\n\nYou can set startup arguments by using variable `KOHYA_ARGS`.\n\nTo manage this service you can use `supervisorctl [start|stop|restart] kohya_ss`.\n\n### Tensorboard\n\nThe service will launch on port `6006` unless you have specified an override with `TENSORBOARD_PORT`.\n\nTo manage this service you can use `supervisorctl [start|stop|restart] tensorboard`.\n\n\u003e[!NOTE]\n\u003eAll services are password protected by default. See the [security](https://github.com/ai-dock/base-image/wiki#security) and [environment variables](https://github.com/ai-dock/base-image/wiki/2.0-Environment-Variables) documentation for more information.\n\n\n## Pre-Configured Templates\n\n**Vast.​ai**\n\n- [Kohya's GUI:latest-cuda](https://link.ai-dock.org/template-vast-kohya_ss)\n\n- [Kohya's GUI:latest-rocm](https://link.ai-dock.org/template-vast-kohya_ss-rocm)\n\n---\n\n_The author ([@robballantyne](https://github.com/robballantyne)) may be compensated if you sign up to services linked in this document. Testing multiple variants of GPU images in many different environments is both costly and time-consuming; This helps to offset costs_","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fai-dock%2Fkohya_ss","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fai-dock%2Fkohya_ss","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fai-dock%2Fkohya_ss/lists"}