[DOC] Improve pipeline() docstrings for config and tokenizer
As currently written, it was not clear to me which arguments were needed when using a non-default model in `pipeline()`. It seemed that when you provided a non-default `model`, that you still needed to manually change the `config` and `tokenizer` because otherwise the "task's default will be used". In practice, though, the pipeline is smart enough to automatically choose the right config/tokenizer for the given model. This PR clarifies that a bit in the docstrings/documentation, by explaining exactly which priorities are used when loading the tokenizer. A small change was made for `config`, too.

Admittedly, the wording for the tokenizer part is a bit off (programmatical, even), but I think it should make clear how the right tokenizer is loaded.

cc @sgugger 
@sgugger I made the change as you requested. Not sure why CI is failing on build_doc. Seems to have to do with some env installation.<|||||>The failure is spurious (basically the new version of pytorch is not cached on the CI and it fails to download it sometimes). Thanks for th fix!