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ModelSphere

Available

Your own Hugging Face Hub. Change one env var — every client just works.

ModelSphere is an on-premises model and dataset registry that speaks the Hugging Face Hub API on the wire. Set HF_ENDPOINT and every standard client — transformers, datasets, diffusers, huggingface-cli, plain git with LFS — works against your registry without patches. It doubles as a pull-through cache for the public Hub, fetching upstream models lazily or via scheduled prefetch for air-gapped sites, and adds what an enterprise registry needs: OIDC SSO, scoped personal access tokens, organizations, private repos, audit logging, Prometheus metrics, and one-tarball backup and restore.

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Specification

Version
v1.6.4 — generally available
Protocol
Hugging Face Hub API · git over HTTPS and SSH · git-LFS (> 5 GiB via HF multipart)
Modes
Primary registry · pull-through cache · scheduled prefetch
Operations
OIDC · PAT scopes · audit log · Prometheus · one-tarball backup
Languages
English · 简体中文

Proof, not promises

See it in one block.

No proprietary SDKs, no rewrites — ModelSphere meets your tools where they already are.

one env var, every client 
$ export HF_ENDPOINT=https://models.intra.example

# everything downstream just works — no client patches
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B")
# served from your registry; cached from upstream or fully air-gapped▌

Wire-compatible with the Hugging Face Hub API — including git clone and multi-gigabyte LFS transfers.

Capabilities

What ModelSphere gives you

01

Wire-compatible with the Hub

Wire-compatible with huggingface_hub — so transformers, datasets, diffusers, and huggingface-cli work by setting HF_ENDPOINT. No forks, no client patches, no proprietary SDK to adopt.

02

Real git underneath

git clone, git lfs pull, and git lfs push work natively; objects beyond 5 GiB upload via Hugging Face's multipart transfer. Model versioning is git versioning — branches, tags, and commits you already understand.

03

A browsable Hub, not just an API

Beyond the wire protocol, ModelSphere ships a web UI: searchable browse with tag, pipeline, and library filters; rendered model cards; an in-browser file viewer and commit-diff history; discussions and likes. Push over HTTPS or SSH; clone, diff, and review in the browser.

04

Pull-through cache for the public Hub

Point it at huggingface.co and it lazily caches what your team pulls — or prefetch on a schedule for fully air-gapped sites. One registry serves both worlds.

05

Enterprise plumbing included

OIDC SSO, personal access tokens with fine-grained scopes, organizations and teams, public/private repos, an audit log of every change, Prometheus metrics with shipped Grafana dashboards, and backup/restore as a single tarball.

How it works

From public dependency to private registry.

  1. Step 01

    Set HF_ENDPOINT

    One environment variable. Every standard Hugging Face client now talks to your registry instead of the public Hub.

  2. Step 02

    Push, pull, clone

    Upload fine-tunes with huggingface-cli or git-lfs. Pull base models through the built-in cache — lazily, or prefetched for air-gap.

  3. Step 03

    Govern and observe

    OIDC decides who sees what. Tokens are scoped. Every change lands in the audit log; usage lands in Prometheus.

Who it's for

Built for these teams

  • Teams hosting fine-tuned and internal models
  • Air-gapped organizations that still want HF workflows
  • Platform teams centralizing model and dataset storage

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