We’re on a journey to advance and democratize artificial intelligence through open source and open science.

HuggingFace's platform is a resource for developers and researchers working in natural language processing (NLP) and machine learning, offering insights into NLP models, tools, and datasets. Through articles, tutorials, and open-source projects, HuggingFace offers insights into state-of-the-art NLP techniques, transformer architectures, and transfer learning methods. Developers can learn about using pre-trained models, fine-tuning strategies, and deploying NLP applications with HuggingFace's libraries and APIs.

Hugging Face

Open Responses is a new open inference standard initiated by OpenAI and backed by Hugging Face, designed to replace the Chat Completion format for agentic AI workflows. Built on OpenAI's Responses API, it supports text, image, and JSON generation, enables autonomous tool execution, and formalizes agentic loops where models can reason, invoke tools, and complete multi-step tasks. Key features include stateless design, standardized parameters, semantic event streaming, and distinction between internal and external tools. The standard is now available for early access through Hugging Face Inference Providers.

Open Responses: What we need to know

What do we need to know to build with Open Responses?