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Setup and Run Ostris AI-Toolkit UI on Runpod

AI-Toolkit Web UI: A Powerful Interface for Training LoRA

The AI-Toolkit is a powerful interface for training your own LoRA, providing a lot of flexibility and advanced functionality. In this post, we will explore the new web-based UI of AI-Toolkit on Runpod, which offers a clean and easy-to-use interface for training LoRA.

AI-Toolkit Resource

The AI-Toolkit is available on the Github page and is frequently updated by the author, Ostris. The toolkit allows you to train LoRA for any model, but the UI supports Flux 1.0, Flex, Wan2.1 T2V 1.3b, Wan2.1 T2V 14b, and Lumina Image.

Install AI-Toolkit on RunPod

To install AI-Toolkit on RunPod, follow these steps:

  1. Login to your Runpod account and create a new Pod with RunPod Pytorch 2.4.0 and a 24GB VRAM GPU (3090 or 4090) as a minimum.
  2. Setup your Pod with:
    • Container Disk at 100GB
    • Volume Disk at 30GB (or more if you are training larger LoRAs)
    • Expose HTTP 8675 (8888 is default for Jupyter Lab) by adding it with a comma to separate the two ports

Launch AI-Toolkit UI

To launch the AI-Toolkit UI, follow these steps:

  1. Open a new Terminal window and change directory to /workspace/ai-toolkit/ui.
  2. Run the command npm run build_and_start.

Training your LoRA on AI-Toolkit UI

To train your LoRA on AI-Toolkit UI, follow these steps:

  1. Create a Dataset by uploading images with their captions.
  2. Create a Training Job by setting up your preferences, including the choice of trigger word, steps of training, and captions for generating samples.

Conclusion

In this post, we have explored the new web-based UI of AI-Toolkit on Runpod, which offers a clean and easy-to-use interface for training LoRA. We have also covered the steps to install AI-Toolkit on RunPod and launch the UI. With this tutorial, you should be able to start training your own LoRA using the AI-Toolkit UI.

FAQs

Q: What is AI-Toolkit?
A: AI-Toolkit is a powerful interface for training your own LoRA, providing a lot of flexibility and advanced functionality.

Q: What models does AI-Toolkit support?
A: AI-Toolkit supports Flux 1.0, Flex, Wan2.1 T2V 1.3b, Wan2.1 T2V 14b, and Lumina Image.

Q: How do I install AI-Toolkit on RunPod?
A: To install AI-Toolkit on RunPod, follow the steps outlined in this post.

Q: How do I launch the AI-Toolkit UI?
A: To launch the AI-Toolkit UI, follow the steps outlined in this post.

Q: What are the requirements for training LoRA using AI-Toolkit UI?
A: The requirements for training LoRA using AI-Toolkit UI include a 24GB VRAM GPU (3090 or 4090) and a Pod with RunPod Pytorch 2.4.0.

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