A large language model (LLM) is a type of machine learning model designed for understanding, generating, and interacting with human language. These models are trained on extensive datasets containing text from books, articles, websites, and other sources to learn patterns, context, and semantics in language. LLMs are widely used in applications like chatbots, code generation, translation, summarization, and more. They are often built using transformer architectures and are central to the field of generative AI.
Finetune Qwen3, Llama 4, TTS, DeepSeek-R1 & Gemma 3 LLMs 2x faster with 70% less memory! 🦥
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
An open-source RAG-based tool for chatting with your documents.
LLM based autonomous agent that conducts deep local and web research on any topic and generates a long report with citations.
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
Structured Text Generation
The official GitHub page for the survey paper "A Survey of Large Language Models".
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Agent Framework / shim to use Pydantic with LLMs
The most reliable AI agent framework that supports MCP.
Pocket Flow Tutorial Project: Turns GitHub repo into Easy Tutorial with AI
Open Source Neural Machine Translation and (Large) Language Models in PyTorch
Efficient Triton Kernels for LLM Training
YuE: Open Full-song Music Generation Foundation Model, something similar to Suno.ai but open