llms

Large Language Models: In this repository Language models are introduced covering both theoretical and practical aspects.

该仓库主要记录 LLMs 算法工程师相关的顶会论文研读笔记（多模态、PEFT、小样本QA问答、RAG、LMMs可解释性、Agents、CoT）

Build a ChatGPT like LLM from scratch in PyTorch, explained step by step.

🦛 CHONK your texts with Chonkie ✨ Type-friendly, light-weight, fast and super-simple chunking library

Scientific Large Language Models: A Survey on Biological & Chemical Domains

A Chrome extension for asking questions over websites

Efficient visual programming for AI language models

Generative AI Application Builder on AWS facilitates the development, rapid experimentation, and deployment of generative artificial intelligence (AI) applications without requiring deep experience in AI. The solution includes integrations with Amazon Bedrock and its included LLMs, such as Amazon Titan, and pre-built connectors for 3rd-party LLMs.

syftr is an agent optimizer that helps you find the best agentic workflows for your budget.

A curated list of awesome instruction tuning datasets, models, papers and repositories.

A ChatGPT clone built in Reflex

🛰️ 基于真实医疗对话数据在ChatGLM上进行LoRA、P-Tuning V2、Freeze、RLHF等微调，我们的眼光不止于医疗问答

Monocle is a framework for tracing GenAI app code. This repo contains implementation of Monocle for GenAI apps written in Python.

🧠 Guide to Building RAG (Retrieval-Augmented Generation) Applications

Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.

On-device LLM Inference Powered by X-Bit Quantization

"Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation" by Yifan Feng, Hao Hu, Shihui Ying, Xingliang Hou, Shiquan Liu, Mingyuan Yang, Junchang Li, Shaoyi Du, Nanning Zheng, Han Hu, and Yue Gao.

Chrome Extension to Summarize or Chat with Web Pages/Local Documents Using locally running LLMs. Keep all of your data and conversations private. 🔐

Build, evaluate and observe LLM apps

AI agent for Home Assistant — talk to your home, create automations in plain language, analyze cameras with face recognition, and get proactive anomaly alerts. Cloud LLMs or fully local via Ollama.