Tune LLM in few lines of code

Auto Data is a library designed for quick and effortless creation of datasets tailored for fine-tuning Large Language Models (LLMs).

A Gradio web UI for Large Language Models. Supports LoRA/QLoRA finetuning,RAG(Retrieval-augmented generation) and Chat

Unlock the potential of finetuning Large Language Models (LLMs). Learn from industry expert, and discover when to apply finetuning, data preparation techniques, and how to effectively train and evaluate LLMs.

Jupyter notebooks for course Finetuning Large Language Models, taught by Sharon Zhou (Lamini) and Andrew Ng (DeepLearning.AI).

This project enhances the LLaMA-2 model using Quantized Low-Rank Adaptation (QLoRA) and other parameter-efficient fine-tuning techniques to optimize its performance for specific NLP tasks. The improved model is demonstrated through a Streamlit application, showcasing its capabilities in real-time interactive settings.

This repository contains code for fine-tuning the LLama3 8b model using Alpaca prompts to generate Java codes. The code is based on a Google Colab notebook.

Finetuning Starcoder2-3B for Code Completion on a single A100 GPU

A fine tuned model for automatic Question Answer pair generation System using large language models and promptify

Jupyter notebooks from "Finetune LLMs" course at deeplearning.ai

This repo contains influential papers which use finetuning techniques for LLMs for domain specific tasks.

This repository contains some of the most influential papers of on the RLHF technique of fine-tuning LLMs.

(In-progress) Finetuning OpenAI's GPT-3.5-Turbo as a base model on open-source data about the Tampa Bay region to create a chatbot specializing in information on the area!