Hugging Face is the central hub where the AI community hosts models, datasets, and demo apps, and serves them through the Inference API and Spaces. Developers pull weights with the transformers library, run hosted inference for production traffic, train and push checkpoints, and share interactive demos. Because so many AI workflows depend on it, a Hugging Face outage can stall builds, break deployments, and freeze model downloads across teams at once. If you suspect a problem right now, start with the live status verdict and recent user reports at the top of this page, then use the checklist below to narrow down the cause.
Common reasons Hugging Face stops working
- Hub or website down: huggingface.co fails to load, model and dataset pages return errors, or the search and repository browser stop responding.
- Inference API errors: hosted inference endpoints time out, return 503 “model loading” responses for long stretches, or rate-limit your requests.
- Model and dataset download failures:
from_pretrained,huggingface_hub, orgit cloneagainst the LFS storage hangs or aborts mid-transfer. - Spaces not building or loading: a Gradio or Streamlit Space gets stuck building, shows a runtime error, or sleeps and will not wake.
- Authentication problems: an expired or revoked access token, or a recently rotated token, causes 401 or 403 responses on pulls and pushes.
- Git push and upload issues: large-file commits fail because of LFS quota, repository permissions, or storage-side errors.
- Regional or network faults: a CDN edge, DNS, or your corporate proxy and firewall block traffic even when Hugging Face itself is fine.
How to fix Hugging Face when it is not working
- Confirm the scope first. Check the verdict and crowd reports at the top of this page to see whether others are reporting the same trouble, so you know if it is Hugging Face or your own setup.
- Test reachability directly. Open huggingface.co in a fresh browser tab and try a known model page. If the site loads but your code fails, the issue is likely local or token related.
- Check your token. Regenerate your access token in account settings, then refresh it locally with
huggingface-cli loginor by updating theHF_TOKENenvironment variable. - Retry inference with backoff. A cold model returns a loading state; wait and retry with exponential backoff rather than hammering the endpoint, which can trigger rate limits.
- Clear and re-pull caches. A corrupted partial download can persist. Remove the affected entry from your local cache directory and pull again.
- Bypass local network blocks. Try a different network or disable a VPN or proxy to rule out DNS and firewall interference.
- Restart or rebuild a Space. Use the Space’s settings to restart the runtime or trigger a fresh build if it is stuck.
- Wait it out for server-side faults. If the outage is on Hugging Face’s side, queue your jobs and retry once reports settle. For a broader plan, see our guide on what to do when an AI tool is down.
Is Hugging Face down, or is it just you?
Some failures look like an outage but are local. An expired token, a stale cache, a hit rate limit, or a proxy that blocks the Hub will all produce errors while Hugging Face runs normally for everyone else. The fastest tell is to compare your experience with the live reports at the top of this page. If many users are reporting the same symptom at the same time, it is probably a real incident. If reports are quiet and only your requests fail, focus on your token, your cache, and your network path before assuming the platform is down.
How we check Hugging Face
Hugging Face publishes an official status page at status.huggingface.co, and our monitor reads its live status feed directly, so provider-confirmed problems flow into the verdict. On top of that we run our own independent reachability check against Hugging Face from the outside, on a regular interval, and watch for failed responses and elevated latency. We combine that signal with the crowd-sourced user reports submitted on this page, so the verdict reflects both what our monitor sees and what real users are experiencing right now. Full details are in our methodology.
Alternatives to Hugging Face during an outage
If the Hub or its inference is down and you need to keep shipping, several peers can host or run models in the meantime. Replicate runs models behind a simple API, Together AI offers hosted open-model inference, and Groq provides fast inference for supported models. Before you switch, confirm the backup is healthy on its own status page, since outages sometimes overlap across providers. Treat these as a temporary fallback, then return to your primary workflow once Hugging Face recovers.
One Space versus the whole Hub
Hugging Face is several products under one roof: the Hub that hosts models and datasets, Spaces that run interactive demos, and the Inference API and Endpoints for programmatic calls. That breadth matters for status questions, because a single Space being broken is very different from the Hub being down. Spaces go to sleep after inactivity and have to wake up on the next visit, so a demo that shows a building or sleeping state is usually just restarting rather than failing.
On the Inference API, the classic message is “Model is loading,” which appears the first time a model is requested after being idle and clears once it finishes loading. Other friction points are specific too: Git LFS pushes can fail or hang when uploading large model and dataset files, sign-in can break independently of everything else, and a single dataset or model repo can be unavailable while the rest of the Hub is fine.
- A sleeping or building Space is normal, not an outage.
- “Model is loading” means wait and retry, not a failure.
- Git LFS issues usually point to large file uploads, not the Hub itself.