Fine-Tuning Large Language Models

A GitHub project aimed at providing tools and resources for fine-tuning large language models.

Description

This project focuses on enabling fine-tuning of state-of-the-art large language models, including models like Mixtral model and llama.

Features

• Support for fine-tuning various large language model architectures.
• Integration with leading deep learning frameworks such as TensorFlow and PyTorch.
• Pre-trained model checkpoints for easy initialization.
• Example scripts and notebooks for fine-tuning and evaluation.

Installation

To install the project, simply clone the repository and install the dependencies:

git clone https://github.com/your-username/your-project.git

Usage

To fine-tune a large language model, follow these steps:

1. Prepare your dataset according to the required format. The format should be jsonl
2. Run the fine-tuning script, specifying the model architecture and hyperparameters.
3. Evaluate the fine-tuned model using the provided evaluation scripts.
4. Utilize the fine-tuned model for inference or downstream tasks.

Contributing

We welcome contributions from the community!

License

This project is licensed under the MIT License. See the LICENSE file for details.

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