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A newer version of the Gradio SDK is available: 5.20.0

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metadata
license: apache-2.0
sdk: gradio
colorFrom: green
colorTo: purple
title: Transformers Fine Tuner
emoji: ⚡
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/64fbe312dcc5ce730e763dc6/EgMfbe-SvtWnERIw6k27e.png
short_description: 'Transformers Fine Tuner: A user-friendly Gradio interface'
sdk_version: 5.17.1

Transformers Fine Tuner

Transformers Fine Tuner is a user-friendly Gradio interface that enables seamless fine-tuning of pre-trained transformer models on custom datasets.

Features

  • Easy Dataset Integration: Load datasets via URLs or direct file uploads.
  • Model Selection: Choose from a variety of pre-trained transformer models.
  • Customizable Training Parameters: Adjust epochs, batch size, and learning rate to suit your needs.
  • Real-time Monitoring: Track training progress and performance metrics.

Setup

  1. Clone the repository:

    git clone https://github.com/canstralian/Transformers-Fine-Tuner.git
cd Transformers-Fine-Tuner

  2. Create and activate a virtual environment:

    python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

  3. Install the required dependencies:

    pip install -r requirements.txt

Usage

To launch the Gradio interface, run the following command:

python app.py

Example

  1. Enter the URL of your dataset.
  2. Select a pre-trained transformer model from the dropdown.
  3. Adjust the training parameters such as epochs, batch size, and learning rate.
  4. Click the "Submit" button to start the fine-tuning process.

File Structure

  • app.py: Main script to launch the Gradio interface.
  • data/preprocess.py: Script to load and preprocess datasets.
  • .github/workflows/python-app.yml: GitHub Actions workflow for CI/CD pipeline.

Contributing

If you would like to contribute to this project, please fork the repository and submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Acknowledgements

This project uses the following libraries and frameworks:

Contact

For any inquiries or support, please contact the repository owner at canstralian.