Use min version for huggingface-hub dependency
Author: lewtun
Pull request: yes

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This PR proposes to use a min version for the `huggingface_hub` dependency. 

The reasoning behind this is that we're currently running into dependency conflicts between `autonlp` (which uses `transformers` v4.8.0) and `evaluate` which relies on `huggingface_hub` v0.0.15. If I am not mistaken, setting a min version will provide the flexibility for `pip` to figure out which one to pick.

I realise that `huggingface_hub` is under active development, so feel free to close this PR if there's a strong need to freeze the version explicitly in `transformers`.

cc @abhishekkrthakur @SBrandeis 


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Comments:
Yes the exact pin has been set on purpose because `huggingface_hub` is not stable enough right now, and there might breaking changes in the future that would break older versions of Transformers.

We can accept an upgrade on the Transformers side (bumping to 0.0.15) but we will only switch to a minimum version when `huggingface_hub` is more mature.

Also, for something like this, no merge before @LysandreJik is back please, as he knows more than me (and may have a different opinion) :-)

Thanks for the clarification @sgugger! I totally understand the reasoning to pin the exact version, so will find a work around in the meantime.

I'll keep this PR open until @LysandreJik is back in case he wants to accept a bump to v0.0.15 😃 

i found a work around using the `/datasets` endpoint so happy to close this PR until `huggingface_hub` is more stable

Just checked, and it should be fine to bump to 0.0.15. Most of the `huggingface_hub` specifics in `transformers` is using the logic defined in `src/transformers/hf_api.py`, so close to nothing would be affected by that upgrade.

Feel free to upgrade and merge if all tests pass, I'll keep a close eye on the slow tests.