Changelog

You can now mount HF Buckets as persistent storage volumes directly in your Spaces. In Space settings, the new "Storage Buckets" section lets you create or select a bucket, set the mount path and access mode. You can also attach a bucket when creating a new Space.

Useful for caching model weights, storing user uploads, or sharing files between Spaces under the same organization.

You can now attach any Storage Bucket, model or dataset from the Hub as a local filesystem. It allows you to attach remote storage that is 100x bigger than your local machine's disk. This is also perfect for Agentic storage! Read-write for Storage Buckets, read-only for models and datasets.

Get started by installing hf-mount from the GitHub repo: https://github.com/huggingface/hf-mount

You can now set your Spaces to protected, making them private on Hugging Face while still keeping their URL publicly accessible.

This is useful for deploying production-ready demos or internal tools without exposing model weights, prompts, or proprietary logic.

Combined with custom domains you can also host your website on Hugging Face.

When AI agents such as Cursor or Claude Code fetch a Hugging Face Papers page, Markdown versions are served automatically, saving tokens and improving efficiency — e.g. huggingface.co/papers/2601.15621.md.

A new hugging-face-paper-pages skill for AI agents lets agents search papers by title, author, or semantic similarity, read their content, and discover linked models, datasets, and Spaces on the Hub.

User and organization settings now include a Repositories page to visualize repository storage consumption. This update makes it easier to monitor usage, understand how storage is distributed across repositories, and manage resources more effectively.