[WIP] Tail free sampling implementation
Author: vfbd
Pull request: yes

# What does this PR do?

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Implements tail free sampling as requested by feature request issue #13784. This pull request currently only contains a PyTorch implementation of tail free sampling because I only know PyTorch and not TensorFlow or Flax and I would not like to waste my time learning those if people do not like this pull request. I can create those implementations on demand.


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Comments:
Thanks for your PR @vfbd! 

Could you maybe give a couple of examples using "GPT2" where tail free sampling works better than `top_k` and `top_p`? :-)

I do not have a concrete text example at the moment, but I do like to weigh in on the matter.

This request is desired by the KoboldAI community after being implemented by community request using finetune's fork as the basis. Users have reported to us that it works preferably for them on longer going stories. While I no longer have the output I also had an instance where switching to TFS is beneficial to the story quality when a GPT model is drawing in undesirable elements such as training data unrelated to the story. Having the ability to switch over can nudge the AI in a more preferable interpretation where you can continue a story that otherwise would have gotten stuck.

Because its an existing community currently relying on forks to facilitate all the features that they have gotten accustomed to and enjoy it would help us a lot if we can give them the experiences and flexibility they desire without having to rely on downstream forks and their maintainers to keep compatibility.

For now our users either run on Finetuneanon's fork, or on the fork related to this pull request so that their features work as expected. We'd like to migrate to the upstream versions and the lack of TFS is currently the main blocker.

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.