---
title: Wan LoRA Trainer
sdk: docker
---

# Wan 2.1 LoRA Trainer

This Space provides a ready-to-use environment for training a LoRA adapter for the Wan 2.1 image-to-video model.

## How it Works

*   **Self-Contained:** All required models are stored directly within this Space for maximum reliability.
*   **Automatic Startup:** When the Space builds, it automatically executes the `start.sh` script to begin the training process. You can monitor the progress in the "Logs" section.

## How to Train on Your Own Data

This Space is pre-configured to run with a test dataset. To train on your own data, simply upload your dataset files, create a `.toml` configuration file for it, and update the `start.sh` script to point to your new config.
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# Wan 2.1LoRA Trainer

This Space runs the Wan 2.1 LoRA training script.
The required models are linked via the repository configuration above.
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# Simple GUI for [Musubi Tuner](https://github.com/kohya-ss/musubi-tuner) (Wan 2.1 models only)


# How to use GUI

- Download the repository by running in the command line:
`git clone https://github.com/Kvento/musubi-tuner-wan-gui`

- To open the GUI just run `Start_Wan_GUI.bat`.
- All settings can be saved and loaded using the "**Load Settings**" and "**Save Setting**" buttons.
- More info about settings see in [Wan2.1 documentation](./docs/wan.md), [Advanced Configuration](./docs/advanced_config.md#fp8-quantization), [Dataset configuration guide](./dataset/dataset_config.md).