https://github.com/ai-dock/onetrainer
OneTrainer docker images for use in GPU cloud and local environments. Includes AI-Dock KDE Plasma desktop with GPU acceleration and audio for authentication and improved user experience.
https://github.com/ai-dock/onetrainer
cloud docker gpu image-generation model-training onetrainer runpod stable-diffusion training vast
Last synced: 26 days ago
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OneTrainer docker images for use in GPU cloud and local environments. Includes AI-Dock KDE Plasma desktop with GPU acceleration and audio for authentication and improved user experience.
- Host: GitHub
- URL: https://github.com/ai-dock/onetrainer
- Owner: ai-dock
- License: other
- Created: 2024-03-07T13:09:07.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-03T23:18:48.000Z (over 1 year ago)
- Last Synced: 2024-05-21T03:07:04.357Z (over 1 year ago)
- Topics: cloud, docker, gpu, image-generation, model-training, onetrainer, runpod, stable-diffusion, training, vast
- Language: Shell
- Homepage:
- Size: 661 KB
- Stars: 6
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE.md
Awesome Lists containing this project
README
[](https://github.com/ai-dock/onetrainer/actions/workflows/docker-build.yml)
# Ai-Dock + OneTrainer Docker Image
Run [OneTrainer](https://github.com/Nerogar/OneTrainer) in a docker container locally or in the cloud.
This image is an extension of [Ai-Dock/Linux-Desktop](https://github.com/ai-dock/linux-desktop) with OneTrainer preinstalled for user convenience.
These container images are tested extensively at [Vast.ai](https://link.ai-dock.org/template-vast-onetrainer) & [Runpod.io](https://link.ai-dock.org/template-runpod-onetrainer) but compatibility with other GPU cloud services is expected.
>[!NOTE]
>These images do not bundle models or third-party configurations. You should use a [provisioning script](#provisioning-script) to automatically configure your container. You can find examples in `config/provisioning`.
## Documentation
All 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) and [runpod.io](https://link.ai-dock.org/template) as straightforward and user friendly as possible.
Common 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.
#### Version Tags
The `:latest` tag points to `:latest-cuda`
Tags follow these patterns:
##### _CUDA_
- `:pytorch-[pytorch-version]-py[python-version]-cuda-[x.x.x]-base-[ubuntu-version]`
- `:latest-cuda` → `:pytorch-2.1.2-py3.10-cuda-11.8.0-base-22.04`
- `:latest-cuda-jupyter` → `:jupyter-pytorch-2.1.2-py3.10-cuda-11.8.0-base-22.04`
Browse [here](https://github.com/ai-dock/onetrainer/pkgs/container/onetrainer) for an image suitable for your target environment.
Supported Python versions: `3.10`
Supported Pytorch versions: `2.1.2`, `2.2.0`
Supported Platforms: `NVIDIA CUDA`
## Additional Environment Variables
| Variable | Description |
| ------------------------ | ----------- |
| `AUTO_UPDATE` | Update OneTrainer on startup (default `true`) |
| `ONETRAINER_BRANCH` | OneTrainer branch/commit hash. (default `master`) |
| `ONETRAINER_FLAGS` | Startup flags. eg. `--generic-option1 --generic-option2` |
See the base environment variables [here](https://github.com/ai-dock/base-image/wiki/2.0-Environment-Variables) for more configuration options.
### Additional Micromamba Environments
| Environment | Packages |
| -------------- | ----------------------------------------- |
| `onetrainer` | OneTrainer and dependencies |
This micromamba environment will be activated on shell login.
See the base micromamba environments [here](https://github.com/ai-dock/base-image/wiki/1.0-Included-Software#installed-micromamba-environments).
## Pre-Configured Templates
**Vast.ai**
- [onetrainer:latest](https://link.ai-dock.org/template-vast-onetrainer)
---
**Runpod.io**
- [onetrainer:latest](https://link.ai-dock.org/template-runpod-onetrainer)
---
_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_