Hugging Face

2025Hugging Faceopen source

Hugging Face Skills

v0.1.0
AI Agents

Hugging Face Skills are Agent Context Protocol (ACP) definitions for AI/ML tasks like dataset creation, model training, and evaluation. They are interoperable with all major coding agent tools like OpenAI Codex, Anthropic's Claude Code, Google DeepMind's Gemini CLI, and Cursor.

Interoperable with major coding agent tools
Self-contained folders with instructions, scripts, and resources
Compatible with Claude Code, Codex, and Gemini CLI
pricingFree
version0.1.0
2026Hugging Faceopen source

Storage Buckets

v1.0
Agentic AI
Infrastructure

Storage Buckets is a feature introduced by Hugging Face to provide mutable, S3-like object storage on the Hugging Face Hub. Designed for machine learning workflows, it allows users to store models, datasets, and artifacts without the overhead of version control. Built on the Xet storage backend, it offers efficient deduplication and fast data transfers.

Mutable, S3-like object storage
Efficient deduplication with Xet backend
Fast data transfers with built-in CDN
version1.0
regionUnited States
2026Hugging Facepaid

physics-intern

vinitial release
AI Agents
Physics

An autonomous agentic framework for physics research built by David Louapre (Hugging Face AI Scientist). Accepts theoretical physics questions in plain text, automatically breaks problems into steps, assigns specialized sub-agents, and reasons through solutions step by step.

Breaks complex theoretical physics problems into sub-steps and assigns specialized reasoning agents
Fully autonomous multi-step reasoning without human intervention between steps
Built by David Louapre (Hugging Face AI Scientist & Science Étonnante YouTube creator with 1.5M subs)
pricingFree (open source / Hugging Face Space)
versioninitial release
2026Hugging Faceopen source

Daggr

vBeta
Open Source
Agentic AI

Daggr is an open-source Python library designed to streamline the creation of AI workflows by connecting Gradio apps, machine learning models, and custom functions. It automatically generates a visual canvas for inspecting intermediate outputs, rerunning individual steps, and managing state within complex pipelines, all through concise Python code.

Visualizes code flow with an automatically generated canvas
Allows inspection and rerunning of individual steps without executing the entire pipeline
Seamlessly integrates with Gradio Spaces, enabling the use of public or private Spaces as nodes in workflows
pricingFree
versionBeta