Hugging Face

HuggingChat is a free, open-source, ChatGPT-style interface by Hugging Face letting you interact with hundreds of open-source LLMs, image models, documentation tools, and agent tools via Model Context Protocol (MCP) servers. Features Omni Smart Routing automatically picking the best AI model for optimal answers. Choose from any available open source models to chat directly. Supports Model Context Protocol servers with OpenAI function calling for tool use. File and image processing for data analysis, document reading, and image recognition. Search functionality enables looking up latest facts online when model lacks up-to-date information. Create custom AI assistants. Democratizes AI making advanced capabilities accessible to extensive user base. Completely free with no limits.

FineWeb is Hugging Face's open 15-trillion-token dataset of cleaned, deduplicated Common Crawl web text, with a curated FineWeb-Edu subset. It is a high-quality, permissively licensed corpus for training modern LLMs.

Gradio is an open-source Python library for quickly building demos and web applications for ML models, APIs, or any Python function. No JavaScript, CSS, or web hosting experience needed. Reached 1 million monthly developers in 2025. Features server-side rendering (v5.0) for faster page loads, sophisticated queuing for GPU-intensive workloads, streaming with Python generators, and seamless HuggingFace Spaces deployment. Deploy to HuggingFace for free with special Model Hub integration. Over 41,000 GitHub stars. Perfect for rapid ML prototyping and sharing.

The Hugging Face Hub is the central platform for sharing and discovering open models, datasets, and Spaces (demos), with versioning, an inference API, and libraries that make loading and deploying AI artifacts trivial.

PEFT is Hugging Face's library for parameter-efficient fine-tuning methods like LoRA, QLoRA, and prompt tuning, letting you adapt large models by training a tiny fraction of parameters on modest hardware.

TRL is Hugging Face's library for post-training transformer models with supervised fine-tuning, reward modeling, and preference optimization (DPO, GRPO, PPO), integrated with the Transformers and PEFT ecosystem.

Text Generation Inference (TGI) is Hugging Face's production-grade toolkit for serving open LLMs, with tensor parallelism, continuous batching, quantization, and an OpenAI-compatible API for high-throughput deployment.

Transformers is Hugging Face's model-definition framework for state-of-the-art machine learning in text, vision, audio, and multimodal models for both inference and training. Supports 300+ model architectures with 3 new architectures added weekly. Over 1M+ model checkpoints on Hugging Face Hub. Transformers v5 (2025) narrows to PyTorch as primary backend for deeper optimization, introduces 'transformers serve' for OpenAI-compatible API deployment, and enhances inference with streamlined APIs, continuous batching, and paged attention. Over 1.2 billion total installs with 3 million daily installations.

smolagents is Hugging Face's minimalist agent library where agents write their actions as Python code. Small, hackable core with support for any LLM, tool calling, and sandboxed code execution.