---
license: creativeml-openrail-m
language:
- en
pretty_name: f
---
# **RT Finetuning Scripts**

*⚠️Clear Notebook Before Use*

This repository contains the training and fine-tuning scripts for the following models and adapters:

- **Llama**
- **Qwen**
- **SmolLM**
- **DeepSeek**
- **Other Adapters**

## Overview

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.

## Features

- **Training Scripts**: Easily train models on your own dataset.
- **Fine-Tuning Scripts**: Fine-tune pre-trained models with minimal setup.
- **Support for Multiple Models**: The scripts support a variety of models including Llama, Qwen, SmolLM, and DeepSeek.
- **Adapter Support**: Fine-tune adapters for flexible deployment and specialization.

## Requirements

Before running the scripts, make sure you have the following dependencies:

- Python 3.x
- `transformers` library
- `torch` (CUDA for GPU acceleration)
- Additional dependencies (see `requirements.txt`)

## Installation

Clone the repository and install dependencies:

```bash
git clone https://github.com/your-repo/rt-finetuning-scripts.git
cd rt-finetuning-scripts
pip install -r requirements.txt
```

## Usage

### Fine-Tuning a Model

1. **Choose a model**: Select from Llama, Qwen, SmolLM, or DeepSeek.
2. **Prepare your dataset**: Ensure your dataset is formatted correctly for fine-tuning.
3. **Run the fine-tuning script**: Execute the script for your chosen model.

## Contributing

Contributions are welcome! If you have improvements or bug fixes, feel free to submit a pull request.