Add unfused clap model for zero-shot

[RahulSChand]

This is a small addition to the #2133 PR. Adds unfused clap model. Test results in the next comment

Code Quality

• [ ✅] Code Formatted: Format the code using make lint to maintain consistent style.

Documentation

• [ ✅] Updated Documentation: Add or update documentation to reflect the changes introduced in this PR.

Testing

• [ ❌] New Tests Added: Write tests to cover new functionality. Validate with make test-with-coverage.
• [ ❌] Tests Passed: Run tests locally using make test or make test-with-coverage to ensure no existing functionality is broken.

Adding datasets checklist

Reason for dataset addition: ...

• I have run the following models on the task (adding the results to the pr). These can be run using the mteb -m {model_name} -t {task_name} command.
  • sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
  • intfloat/multilingual-e5-small
• I have checked that the performance is neither trivial (both models gain close to perfect scores) nor random (both models gain close to random scores).
• If the dataset is too big (e.g. >2048 examples), considering using self.stratified_subsampling() under dataset_transform()
• I have filled out the metadata object in the dataset file (find documentation on it here).
• Run tests locally to make sure nothing is broken using make test.
• Run the formatter to format the code using make lint.

Adding a model checklist

• [ ✅] I have filled out the ModelMeta object to the extent possible
• [ ✅] I have ensured that my model can be loaded using
  • [ ✅] mteb.get_model(model_name, revision) and
  • [ ✅] mteb.get_model_meta(model_name, revision)
• [ ✅] I have tested the implementation works on a representative set of tasks.

[RahulSChand]

Tested with on ESC50

import mteb
model_name = "laion/clap-htsat-unfused"
model = mteb.get_model_meta(model_name=model_name)

tasks = mteb.get_tasks(tasks=["ESC50_Zeroshot"])

evaluation = mteb.MTEB(tasks=tasks)

results = evaluation.run(model)
print(results[0].scores)