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| license: mit | |
| title: Gemma FineTuner | |
| sdk: gradio | |
| emoji: 🔥 | |
| colorFrom: gray | |
| colorTo: green | |
| pinned: true | |
| # Gemma Fine-tuning UI | |
| A user-friendly interface for fine-tuning Google's Gemma models using Unsloth optimizations. | |
| ## Features | |
| - Easy-to-use web interface for model fine-tuning | |
| - Support for multiple data formats (CSV, JSONL, TEXT) | |
| - Parameter-efficient fine-tuning with LoRA | |
| - Real-time training progress visualization | |
| - Model export in multiple formats | |
| - Integrated text generation testing | |
| ## Installation | |
| ```bash | |
| git clone https://github.com/codewithdark-git/Gemma-Finetune.git | |
| cd Gemma-Finetune | |
| pip install -r requirements.txt | |
| ``` | |
| ## Usage | |
| 1. Run the application: | |
| ```bash | |
| python main.py | |
| ``` | |
| 2. Follow the UI steps: | |
| - Upload your dataset | |
| - Configure model parameters | |
| - Start training | |
| - Test and export your model | |
| ## Requirements | |
| See requirements.txt for detailed dependencies. | |
| ## License | |
| MIT License |