Tutorial on training, evaluating LLM, as well as utilizing RAG, Agent, Chain to build entertaining applications with LLMs.分享如何训练、评估LLMs,如何基于RAG、Agent、Chain构建有趣的LLMs应用。
MIT License
LLM Finetuning with peft
Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A
telegram bot for self-hosted local inference of stable diffusion, text-to-speech and large langua...
Yet another `llama.cpp` Rust wrapper
RAG using Llama3, Langchain and ChromaDB
LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with cus...
This repository contains a web application designed to execute relatively compact, locally-operat...
Llama中文社区,Llama3在线体验和微调模型已开放,实时汇总最新Llama3学习资料,已将所有代码更新适配Llama3,构建最好的中文Llama大模型,完全开源可商用
Development and deployment of a question-answer LLM model using Llama2 with 7B parameters and RAG...
PHP examples about the usage of GenAI and LLM
A simple, intuitive toolkit for quickly implementing LLM powered applications.
Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of th...
The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models ...
Query LLM with Chain-of-Tought
LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable fo...