Adding ZeroShotImageClassificationPipeline
Author: Narsil
Pull request: yes

# What does this PR do?

- Based on CLIP
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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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- [ ] Did you write any new necessary tests?


## Who can review?

@suraj-patil @LysandreJik

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

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Comments:
Pinging @patil-suraj @LysandreJik 

Friendly ping @LysandreJik  @patil-suraj

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.

unstale?

> This is looking good, thanks a lot for adding this! Left a few comments.

Thanks for this, many places where doc/code was out of sync/bad copy paste here.

> Could you explain a bit how batching is handled ?

https://github.com/huggingface/transformers/pull/14225

This should contain more information on how it's handled internally. The pseudo code and images try to convey how it's done.
Tell me how this could be improved, it should belong in the doc actually.

@LysandreJik Can you do a second quick review please ? I think adding new pipeline merits a bit more eyes than 4.

@patil-suraj Do you think we can add a sigmoid to get `multi_label` or are the outputs of the model not compatible with this ?
@FrancescoSaverioZuppichini 

> @patil-suraj Do you think we can add a sigmoid to get `multi_label` or are the outputs of the model not compatible with this ? @FrancescoSaverioZuppichini

Technically, yes. But I don't know how well that will work.

Ok let's drop it then. I actually thought  about it with maybe multiple prompts too (This photo is about ..., This photo is not about ...) to recover somehow the entailment thing, but CLIP was not trained with this in mind so let's just skip it.)


@LysandreJik friendly ping to get a third opinion before merging.

After thinking about it, sigmoid won't probably work well since it wasn't trained directly with it. We could (in theory) normalize the `image_logits` and return the ones that are more close to biggest other (meaning they all "fit" the image in the same way). Following @patil-suraj comment, I'm not sure how well this works either.

time to continue the widget PR? https://github.com/huggingface/huggingface_hub/pull/118 😊