Allow users to force TF availability
We have a user report that with custom Tensorflow builds and package names that  `_tf_available` can return `False` even if `import tensorflow` succeeds, because the user's package name isn't in the [allowed list](https://github.com/huggingface/transformers/blob/02b176c4ce14340d26d42825523f406959c6c202/src/transformers/utils/import_utils.py#L63L75). 

This is quite niche, so I don't want to do anything that could affect other users and workflows, but I added a `FORCE_TF_AVAILABLE` envvar that will skip version checks and just make sure TF is treated as available. @sgugger WDYT, or is there a better solution?

Fixed #18642 
_The documentation is not available anymore as the PR was closed or merged._<|||||>Ah, additional nit: I'd document this somewhere.<|||||>@LysandreJik I think a lot of these envvars aren't documented anywhere - I can't see any documentation for USE_TF or USE_TORCH! Maybe we should make a separate docs PR with a list of envvars that `transformers` uses?<|||||>That would be fantastic :) 

Thanks for your contribution, merging!