Namespace Objects for Search Parameters

[muellerzr]

PR that adds the following:

Namespace Objects for Search Parameters

With a goal of adding more tab-completion to the library, this PR introduces two objects:

• DatasetSearchArguments
• ModelSearchArguments
  These two AttributeDictionary objects contain all the valid information we can extract from a model as tab-complete parameters. We also include the author_or_organization and dataset (or model) _name as well through careful string splitting.

Tests Added:

Considering there is nothing "new" done in DatasetSearchArguments that isn't already tested in DatasetTags or AttributeDictionary.search I chose not to add any tests here (especially because each call to the SearchArguments() classes calls the api twice)

If tests are wanted, I can include them.

[muellerzr]

Realized I never quite said how they're related. It's a quality of life need for our users. For example, say I want to use the ModelSearchArguments, and I'd like to know if there are models with resnet I can use. I do:

args = ModelSearchArguments()
args.model_name.search("resnet")

To return all of the models that contain the name resnet

(This then trickles to anything using AttributeDictionary too)

[LysandreJik]

Cool, I like this a lot. Thanks for iterating with me on this, I think this should provide some very useful tooling for the model_list/dataset_list, and should provide a good platform on which we can build some useful methods in transformers and others.

[LysandreJik]

As said offline; the search argument was a bit overkill for a first version, so thanks for removing it for now. I think these namespaces are quite simple and can be further iterated once we identify community usage/requests.