Fei Tang's starred repositories
ChatGPT-Next-Web
A cross-platform ChatGPT/Gemini UI (Web / PWA / Linux / Win / MacOS). 一键拥有你自己的跨平台 ChatGPT/Gemini 应用。
ChatGLM-6B
ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型
ColossalAI
Making large AI models cheaper, faster and more accessible
llama_index
LlamaIndex is a data framework for your LLM applications
stanford_alpaca
Code and documentation to train Stanford's Alpaca models, and generate the data.
Mr.-Ranedeer-AI-Tutor
A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.
NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
ml-stable-diffusion
Stable Diffusion with Core ML on Apple Silicon
alpaca.cpp
Locally run an Instruction-Tuned Chat-Style LLM
PaLM-rlhf-pytorch
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
chatgpt-web-share
ChatGPT Plus 共享方案。ChatGPT Plus / OpenAI API sharing solution.
researchgpt
A LLM based research assistant that allows you to have a conversation with a research paper
vim-illuminate
illuminate.vim - (Neo)Vim plugin for automatically highlighting other uses of the word under the cursor using either LSP, Tree-sitter, or regex matching.
chatgpt-web
ChatGPT web interface using the OpenAI API
distilabel
⚗️ distilabel is a framework for synthetic data and AI feedback for AI engineers that require high-quality outputs, full data ownership, and overall efficiency.
dr-doc-search
Converse with book - Built with GPT-3
llm-autoeval
Automatically evaluate your LLMs in Google Colab
stable-diffusion-deploy
Learn to serve Stable Diffusion models on cloud infrastructure at scale. This Lightning App shows load-balancing, orchestrating, pre-provisioning, dynamic batching, GPU-inference, micro-services working together via the Lightning Apps framework.
sota-extractor
The SOTA extractor pipeline
Compute-Trends
Supplementary material for our paper "Compute Trends Across Three Eras of Machine Learning".