Update README.md

README.md

@@ -1,3 +1,5 @@
+---
+
 # 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.
@@ -12,4 +14,60 @@ Transformers Fine Tuner is a user-friendly Gradio interface that enables seamles
 ## Setup
 
 1. Clone the repository:
-
+    ```bash
+    git clone https://github.com/canstralian/Transformers-Fine-Tuner.git
+    cd Transformers-Fine-Tuner
+    ```
+
+2. Create and activate a virtual environment:
+    ```bash
+    python -m venv venv
+    source venv/bin/activate  # On Windows use `venv\Scripts\activate`
+    ```
+
+3. Install the required dependencies:
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+## Usage
+
+To launch the Gradio interface, run the following command:
+```bash
+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](LICENSE) file for more details.
+
+## Acknowledgements
+
+This project uses the following libraries and frameworks:
+- [Gradio](https://gradio.app/)
+- [Hugging Face Transformers](https://huggingface.co/transformers/)
+- [Pandas](https://pandas.pydata.org/)
+
+## Contact
+
+For any inquiries or support, please contact the repository owner at [canstralian](https://github.com/canstralian).
+
+---
+