File size: 1,782 Bytes
a0dd7d3 3edfc92 c57def1 a0dd7d3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
---
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. |