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.
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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
- Updated Feb 19, 2026
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a.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
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Production-ready platform for agentic workflow development.
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🦜🔗 The platform for reliable agents.
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User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
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Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
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🔥 The Web Data API for AI - Turn entire websites into LLM-ready markdown or structured data
- Updated Feb 19, 2026
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🌐 Make websites accessible for AI agents. Automate tasks online with ease.
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Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
- Updated Feb 5, 2026
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
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A high-throughput and memory-efficient inference and serving engine for LLMs
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🙌 OpenHands: AI-Driven Development
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Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
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🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
- Updated Jan 21, 2026
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Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
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The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.
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Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train OpenAI gpt-oss, DeepSeek, Qwen, Llama, Gemma, TTS 2x faster with 70% less VRAM.
- Updated Feb 19, 2026
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Complete Claude Code configuration collection - agents, skills, hooks, commands, rules, MCPs. Battle-tested configs from an Anthropic hackathon winner.
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Universal memory layer for AI Agents
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