• AlpacaEval Leaderboard - An Automatic Evaluator for Instruction-following Language Models
• Open LLM Leaderboard - aims to track, rank and evaluate LLMs and chatbots as they are released.
• Open Ko-LLM Leaderboard - The Open Ko-LLM Leaderboard objectively evaluates the performance of Korean Large Language Model (LLM).
• Yet Another LLM Leaderboard - Leaderboard made with LLM AutoEval using Nous benchmark suite.
• Open LLM Leaderboard - aims to track, rank and evaluate LLMs and chatbots as they are released.
• Chatbot Arena Leaderboard - a benchmark platform for large language models (LLMs) that features anonymous, randomized battles in a crowdsourced manner.
• OpenCompass 2.0 LLM Leaderboard - OpenCompass is an LLM evaluation platform, supporting a wide range of models (InternLM2,GPT-4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.

Kaggle & Colab Notebooks

• Prompting Llama 3 like a Pro
• LLaVa via Ollama - Image Annotation

Courses & Lectures

• Stanford
• UWaterloo

Blogs

• InternVL
• InternLM2
• Qwen
• Mistral 7B
• Vicuna-13B - source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
• OPT - trained Transformer Language Models by Meta AI. OPT is a series of open-sourced large causal language models which perform similar in performance to GPT3.
• Gemma - based large language model developed by Google AI (2B, 7B).
• Chinchilla
• Mistral AI
• Adept
• Fuyu
• PanGu-α - PanGu-α is a 200B parameter autoregressive pretrained Chinese language model develped by Huawei Noah's Ark Lab, MindSpore Team and Peng Cheng Laboratory.

Multi-Modal LLMs

• LLaVA
• Flamingo

Embedding

• Code
• Code

Generation

• Code
• Project
• Project - wu/SLD)
• Project

Unerstanding

• Code
• Project

Papers

• Project - AI-Lab/Mantis)
• Project
• OpenAI

Frameworks

• Ollama
• LlamaIndex
• Petals - style. Fine-tuning and inference up to 10x faster than offloading. (7768 stars)
• LLaMA-Factory - to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM3). (5532 stars)
• H2O LLM Studio - code GUI for fine-tuning LLMs. Documentation: [https://h2oai.github.io/h2o-llmstudio/](https://h2oai.github.io/h2o-llmstudio/) (2880 stars)
• Phoenix - Evaluate, troubleshoot, and fine tune your LLM, CV, and NLP models in a notebook. (1596 stars)
• LLM-Adapters - Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models". (769 stars)
• Platypus - tuning Platypus fam LLMs using LoRA. (589 stars)
• xtuner - tuning LLM (InternLM, Llama, Baichuan, QWen, ChatGLM2). (540 stars)
• DB-GPT-Hub - tuning techniques for DB-GPT, with the purpose of enhancing model performance, especially in Text-to-SQL, and achieved higher exec acc than GPT-4 in spider eval with 13B LLM used this project. (422 stars)
• LLM-Finetuning-Hub - tuning and deployment scripts along with our research findings. :star: 416
• Finetune_LLMs - tuning Casual LLMs. :star: 391
• llmware - grade LLM-based development framework, tools, and fine-tuned models. :star: 289
• LLM-Kit
• h2o-wizardlm - Source Implementation of WizardLM to turn documents into Q:A pairs for LLM fine-tuning. :star: 228
• hcgf - model Fine-tuning | LLM微调. :star: 196
• llm_qlora - tuning LLMs using QLoRA. :star: 136
• awesome-llm-human-preference-datasets - tuning, RLHF, and eval. :star: 124
• llm_finetuning - tuning and inference of Large Language Models (LLMs) with several quantization techniques (GTPQ, bitsandbytes). :star: 114
• lit-gpt - of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. (3469 stars)
• LLM-Finetuning-Hub - tuning and deployment scripts along with our research findings. :star: 416
• MFTCoder - task fine-tuning framework for Code LLMs; 业内首个高精度、高效率、多任务、多模型支持、多训练算法，大模型代码能力微调框架. :star: 337

Frameworks

• Awesome-LLM-3D
• Awesome LLMs Fine-Tuning
• Awesome-LLM

Frameworks

• LLaMA Efficient Tuning - to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon).
• H2O LLM Studio - code GUI for fine-tuning LLMs.
• PEFT - Efficient Fine-Tuning (PEFT) methods for efficient adaptation of pre-trained language models to downstream applications.
• ChatGPT-like model - like model locally on your device.
• Petals - 176B collaboratively, allowing you to load a small part of the model and team up with others for inference or fine-tuning. 🌸
• NVIDIA NeMo - of-the-art conversational AI models and specifically designed for Linux. 🚀
• H2O LLM Studio - code GUI tool for fine-tuning large language models on Windows. 🎛️
• Ludwig AI - code framework for building custom LLMs and other deep neural networks. Easily train state-of-the-art LLMs with a declarative YAML configuration file. 🤖
• bert4torch - source large model weights for reasoning and fine-tuning. 🔥
• Alpaca.cpp - like model locally on your device. A combination of the LLaMA foundation model and an open reproduction of Stanford Alpaca for instruction-tuned fine-tuning. 🦙
• promptfoo