finetune-llm

FineTune LLMs in few lines of code (Text2Text, Text2Speech, Speech2Text)

Querypls🛠️: WebApp that Simplify SQL with Your Prompts. Transforming questions into SQL commands effortlessly.

Fine-tuning Qwen2.5-VL for vision-language tasks | Optimized for Vision understanding | LoRA & PEFT support.

Gen AI Large Language Model Projects

使用LLaMA-Factory微调多模态大语言模型的示例代码 Demo of Finetuning Multimodal LLM with LLaMA-Factory

无需预算，使用你的个人数据克隆自己——赛博飞升！Clone yourself by tuning a LLM using your own data.

🎯 Generate fake data for finetune of AI, Just like a person.

这是一个很可爱的色妹妹，送给每一个需要的人~

This repository demonstrates how to fine-tune the Google Gemma 2 2B model to improve its performance on Japanese instruction-following tasks. It serves as a practical guide for developers and researchers interested in adapting large language models for specific languages or domains using state-of-the-art techniques in 2024.

Fine-tune open-source Language Models (LLMs) on E-commerce data, leveraging Amazon's sales data. Showcase a tailored solution for enhanced language understanding and generation with a focus on custom E-commerce datasets.

LLM, Fine Tuning, Llama 2, Gemma, Mixtral, vLLM, LangChain, RAG, ChromaDB, FAISS

Finetune LLaMA-2-7b-chat to perform safety evaluation of user-bot conversation

Dive into the world of Large Language Models (LLMs) with this comprehensive repository. From understanding basics to exploring various LLMs, finetuning on downstream tasks, and deploying models using Vector DBs like Qurant, this guide equips you with essential skills for harnessing the power of LLMs in your projects.

"FASHIO leverages FAISS and advanced NLP for precise fashion recommendations tailored to user preferences."

This is a course projection of finetuning LLM to identify toxic language.

This repository showcases the implementation of the QLoRA Method to fine-tune the Llama language model, enabling efficient deployment of lightweight models for various downstream tasks in natural language processing. Explore advanced techniques for enhancing LLMs in practical applications.

This project explores GPT-2 and Llama models through pre-training, fine-tuning, and Chain-of-Thought (CoT) prompting. It includes memory-efficient optimizations (SGD, LoRA, BAdam) and evaluations on math datasets (GSM8K, NumGLUE, StimulEq, SVAMP).

I’ll be testing different Gemma models and sharing the results here and on my Hugging Face space. Stay tuned for updates!

FineTune Microsoft Phi-2 with your own data

Working on LLMs