llama

The simplest way to run LLaMA on your local machine

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

🤖 Self-hosted, community-driven, local OpenAI-compatible API. Drop-in replacement for OpenAI running LLMs on consumer-grade hardware. Free Open Source OpenAI alternative. No GPU required. LocalAI is an API to run ggml compatible models: llama, gpt4all, rwkv, whisper, vicuna, koala, gpt4all-j, cerebras, falcon, dolly, starcoder, and many other

BELLE: Be Everyone's Large Language model Engine（开源中文对话大模型）

A web interface for chatting with Alpaca through llama.cpp. Fully dockerized, with an easy to use API.

Semantic cache for LLMs. Fully integrated with LangChain and llama_index.

Chinese-Vicuna: A Chinese Instruction-following LLaMA-based Model —— 一个中文低资源的llama+lora方案，结构参考alpaca

A large-scale 7B pretraining language model developed by BaiChuan-Inc.

Large Language-and-Vision Assistant built towards multimodal GPT-4 level capabilities.

Repo for BenTsao [original name: HuaTuo (华驼)], Llama-7B tuned with Chinese medical knowledge. 本草（原名：华驼）模型仓库，基于中文医学知识的LLaMA模型指令微调

Instruction Tuning with GPT-4

Giving Kubernetes Superpowers to everyone

InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)

Database system for building simpler and faster AI-powered applications

Chinese-LLaMA 、Chinese-Falcon 基础模型；ChatFlow中文对话模型；中文OpenLLaMA模型；NLP预训练/指令微调数据集

Easily build, customize and control your own LLMs

AGiXT is a dynamic AI Automation Platform that seamlessly orchestrates instruction management and complex task execution across diverse AI providers. Combining adaptive memory, smart features, and a versatile plugin system, AGiXT delivers efficient and comprehensive AI solutions.

Simple UI for LLM Model Finetuning

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. Meanwhile, we created a new branch to build a Tabular LLM.（我们分别统一了丰富的IFT数据（如CoT数据，目前仍不断扩充）、多种训练效率方法（如lora，p-tuning）以及多种LLMs，三个层面上的接口，打造方便研究人员上手的LLM-IFT研究平台。同时tabular_llm分支构建了面向表格智能任务的LLM。

Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.