Add zero-shot classification

[seanmor5]

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I will add tests tomorrow when I get the multi-prompt case down, but right now it seems to be working fine:

Btw, is there a reason we hid documentation for TokenClassification ?

[jonatanklosko]

Awesome! I think ideally we should follow the same format as image/text classification, so %{predictions: [%{label: ..., score: ...}, ...]}. For now I wouldn't include prompt and label in the output, since the user has the input, and for multiple they can just zip.

Btw, is there a reason we hid documentation for TokenClassification?

We use defdelegate in the Bumblebee.Text module and there are all the docs :)

[jonatanklosko]

@seanmor5 I fixed the post processing to apply softmax per batch on the entailment label. I also adjusted the assertions based on this:

from transformers import pipeline

p = pipeline("zero-shot-classification", model="facebook/bart-large-mnli", candidate_labels=["cooking", "traveling", "dancing"])

p("one day I will see the world")