prithivMLmods
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README.md
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license: creativeml-openrail-m
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---
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license: creativeml-openrail-m
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language:
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- en
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pretty_name: f
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---
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# **RT Finetuning Scripts**
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This repository contains the training and fine-tuning scripts for the following models and adapters:
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- **Llama**
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- **Qwen**
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- **SmolLM**
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- **DeepSeek**
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- **Other Adapters**
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## Overview
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These scripts are designed to help you fine-tune various language models and adapters, making it easy to train or adapt models to new datasets and tasks. Whether you want to improve a model’s performance or specialize it for a specific domain, these scripts will facilitate the process.
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## Features
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- **Training Scripts**: Easily train models on your own dataset.
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- **Fine-Tuning Scripts**: Fine-tune pre-trained models with minimal setup.
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- **Support for Multiple Models**: The scripts support a variety of models including Llama, Qwen, SmolLM, and DeepSeek.
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- **Adapter Support**: Fine-tune adapters for flexible deployment and specialization.
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## Requirements
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Before running the scripts, make sure you have the following dependencies:
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- Python 3.x
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- `transformers` library
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- `torch` (CUDA for GPU acceleration)
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- Additional dependencies (see `requirements.txt`)
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## Installation
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Clone the repository and install dependencies:
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```bash
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git clone https://github.com/your-repo/rt-finetuning-scripts.git
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cd rt-finetuning-scripts
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pip install -r requirements.txt
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```
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## Usage
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### Fine-Tuning a Model
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1. **Choose a model**: Select from Llama, Qwen, SmolLM, or DeepSeek.
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2. **Prepare your dataset**: Ensure your dataset is formatted correctly for fine-tuning.
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3. **Run the fine-tuning script**: Execute the script for your chosen model.
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## Contributing
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Contributions are welcome! If you have improvements or bug fixes, feel free to submit a pull request.
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