Fine_tune_Anything

Fine-Tuning Repository for Causal Language Models

Overview ?

This repository offers tools for fine-tuning causal language models, leveraging the power of the PEFT (PyTorch Efficient Fine-Tuning) library. It's designed for enhancing code generation tailored to specific repositories.

Features

• Model Flexibility ?: Load any causal language model.
• Configuration-Based Setup : Easily define model selection and tokenization through a conf/config.yaml file.
• Efficient Fine-Tuning ?‍♂️: Currently utilizing LoRA (Low-Rank Adaptation) via the PEFT library. More methods coming soon!
• Future-Ready ?: Stay tuned for training methods for instruct and QA models.

Getting Started ?

Prerequisites ?

• Python 3.x ?
• PyTorch
• PEFT Library
• Other dependencies listed in requirements.txt

Installation ?

1. Clone the repository: git clone [repository URL] :git:
2. Make a place for storing data mkdir data make sure to update config.yaml accordingly.
3. Install required packages: pip install -r requirements.txt

Configuration

Tweak the confconfig.yaml file to set your model and tokenization parameters.

Usage

Kick off the fine-tuning process by running the main script (python main.py). Fine tuned model will be saved in directory specified in config.yaml -> "optimization" -> result_dir.

Contributing ?

We welcome your contributions to make this tool even more efficient and feature-rich. Please adhere to standard open-source contribution guidelines.

License ?

Apache License 2.0