Private model inference widget suddenly stopped working
The model interface widget for my model has stopped working on its model page in the hub. When you click “Compute”, the loading progess bar spins for a bit and then it says:Can’t load tokenizer using from_pretrained, please update its configuration:username/modelis not a local folder and is not a valid model identifier listed on ‘Models - Hugging Face’ If this is a private repository, make sure to pass a token having permission to this repo withuse_auth_tokenor log in withhuggingface-cli loginand passuse_auth_token=True.Obviously the model actually exists because this is showing up on its model page, and I’m logged in to the hub because I’m able to see the page.Is this the best place for bug reports like this?
2023-07-18T09:34:14Z
Facing the same issue from July 11th.Not sure on how to report this either
2023-07-18T09:58:14Z
Do you have a public model example that we could examine?
2023-07-18T12:04:13Z
@rockwalrus@valentinaprotti@radamesI have the same problem. The widget worked well until last week. I got the same error.My model is gated. I gave myself access. Same problem… Maybe something change on the inference API?Edit:As of July 18 2023 at 8:30, my widget is back in business!The Inference API just took one week for the Summer holidays. : )
2023-07-19T10:20:59Z
hello all, this was fixed yesterday. thanks for the patience. Please try againgithub.com/huggingface/transformersFixing double `use_auth_token.pop` (preventing private models from being visible).huggingface:main←huggingface:fix_use_auth_tokenopened09:02PM - 13 Jul 23 UTCNarsil+0-1# What does this PR do?

Should fix: https://github.com/huggingface/transforme…rs/issues/14334#issuecomment-1634527833

Repro: Have a private repo, with `vocab.json` (spread out files for the
tokenizer) and use `AutoTokenizer.from_pretrained(...,
use_auth_token="token")`.

Not sure if we already have private visibility tests to maybe add/fix some so we can detect this in our suite.



<!--
Congratulations! You've made it this far! You're not quite done yet though.

Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.

Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change.

Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost.
-->



Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @sgugger

Integrations:

- deepspeed: HF Trainer/Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam

Documentation: @sgugger, @stevhliu and @MKhalusova

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: @sgugger
- TensorFlow: @Rocketknight1

 -->