#Instruction-tuning
Showing 42 of 42 repositories tagged #instruction-tuning, ranked by stars
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
The official GitHub page for the survey paper "A Survey of Large Language Models".
Data processing for and with foundation models! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷
Instruction Tuning with GPT-4
Code and models for ICML 2024 paper, NExT-GPT: Any-to-Any Multimodal Large Language Model
总结Prompt&LLM论文，开源数据&模型，AIGC应用
🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.
InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactions
We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！
mPLUG-Owl: The Powerful Multi-modal Large Language Model Family
Cambrian-1 is a family of multimodal LLMs with a vision-centric design.
Synthetic data curation for post-training and structured data extraction
An Open-sourced Knowledgable Large Language Model Framework.
DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models. 🤖💤
[ICML2024 (Oral)] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation
Generative Representational Instruction Tuning
[ICML 2024] LESS: Selecting Influential Data for Targeted Instruction Tuning
MindSpore online courses: Step into LLM
[CVPR 2025 Highlight] Official code for "Olympus: A Universal Task Router for Computer Vision Tasks"
A minimal codebase for finetuning large multimodal models, supporting llava-1.5/1.6, llava-interleave, llava-next-video, llava-onevision, llama-3.2-vision, qwen-vl, qwen2-vl, phi3-v etc.
Research Trends in LLM-guided Multimodal Learning.
A curated list of awesome instruction tuning datasets, models, papers and repositories.
“百聆”是一个基于LLaMA的语言对齐增强的英语/中文大语言模型，具有优越的英语/中文能力，在多语言和通用任务等多项测试中取得ChatGPT 90%的性能。BayLing is an English/Chinese LLM equipped with advanced language alignment, showing superior capability in English/Chinese generation, instruction following and multi-turn interaction.⚠️ This project has been moved to: https://github.com/BayLing-Models/BayLing
Code/Data for the paper: "LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding"
Datasets for Instruction Tuning of Large Language Models
[ECCV 2024] ShareGPT4V: Improving Large Multi-modal Models with Better Captions
Code for instruction-tuning Stable Diffusion.
Project for the paper entitled `Instruction Tuning for Large Language Models: A Survey`
Awesome LLM Papers and repos on very comprehensive topics.
The ParroT framework to enhance and regulate the Translation Abilities during Chat based on open-sourced LLMs (e.g., LLaMA-7b, Bloomz-7b1-mt) and human written translation and evaluation data.
Resources on Large Language Models for Table Processing
[ICLR 2025] Official implementation of paper "Improving Data Efficiency via Curating LLM-Driven Rating Systems"
An LLM training framework built from the ground up, featuring a custom BumbleBee architecture and end-to-end support for multiple open-source models across Pretraining → SFT → RLHF/DPO.
🚀 Easy, open-source LLM finetuning with one-line commands, seamless cloud integration, and popular optimization frameworks. ✨
[NeurIPS 2023 Main Track] This is the repository for the paper titled "Don’t Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner"
This repo contains a list of channels and sources from where LLMs should be learned
Code and data for "Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation" (EMNLP 2023)
An open-source conversational language model developed by the Knowledge Works Research Laboratory at Fudan University.
Multimodal Instruction Tuning for Llama 3
Implementation of build a LLM from scratch by Sebastian Raschka.