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A ✨ shiny ✨ interface to fine-tune models with Axolotl on HuggingFace

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Note: This is filler text for now, but the app will be a fine-tuning app for Hugging Face models. It will allow users to easily fine-tune models on their own datasets using Hugging Face's infrastructure.

Getting Started with Your Fine-Tuning App on Hugging Face Spaces

Welcome to the fine-tuning app hosted on Hugging Face Spaces! This app leverages the power of Hugging Face's infrastructure to allow you to launch and fine-tune machine learning models easily. Below you'll find a guide to help you get started with using this app.

Step 1: Create a Hugging Face Account

Before you can use the app, you need to have a Hugging Face account. If you don't have one, please sign up at Hugging Face.

Step 2: Launch the App

Once you have an account, navigate to the app hosted on Hugging Face Spaces. You can create a new space for your project directly on your profile or your organization's profile

Step 3: Configure Your Job

In the app, you'll be able to configure your fine-tuning job. This includes selecting the dataset, model, and fine-tuning parameters. If you're not sure about the configurations, the app provides guidance to help you make the best choices for your specific use case.

Step 4: Start Fine-Tuning

With your job configured, you can launch the fine-tuning process. The app will create a new space where your job will run. You can monitor the progress directly within the app.

Step 5: Job Completion and Shutdown

Once the training is complete, the job will automatically shut down. You don't need to worry about stopping the resources manually, as the app handles this for you

Step 6: Review and Download Results

After the job has finished, you can review the results and download any artifacts, such as the fine-tuned model. These will be available in the space created for your job.

Additional Information

Support: If you need help with making a Space or run into any issues, feel free to ask questions on the Hugging Face forum

Upgrades: You can upgrade your Space to run on a GPU or other accelerated hardware if your job requires it. Persistent Storage: If your fine-tuning job requires persistent storage, this can be configured in your Space settings Collaboration: You can work collaboratively with other people in the ML ecosystem by sharing your Space or inviting others to contribute. Conclusion This app is designed to make machine learning more accessible by simplifying the process of launching and fine-tuning models. We hope this guide helps you get started smoothly. Happy fine-tuning!

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