SPARKNLP-635: CLIPForZeroShotClassification

[DevinTDHa]

Description

This PR adds the annotator CLIPForZeroShotClassification.

CLIP (Contrastive Language-Image Pre-Training) is a neural network that was trained on image
and text pairs. It has the ability to predict images without training on any hard-coded
labels. This makes it very flexible, as labels can be provided during inference. This is
similar to the zero-shot capabilities of the GPT-2 and 3 models.

The default model is uploaded at #14082

How Has This Been Tested?

Old and new tests passing.

Screenshots (if appropriate):

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• Code improvements with no or little impact
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)

Checklist:

• My code follows the code style of this project.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.
• I have read the CONTRIBUTING page.
• I have added tests to cover my changes.
• All new and existing tests passed.