feat: add jina-v3 into model list

[bwanglzu]

Checklist

• Run tests locally to make sure nothing is broken using make test.
• Run the formatter to format the code using make lint.

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.

[Samoed]

I'm also working on this in #1319 too, and this implementation isn't quite right because MTEB will generate tasks that don't align with Jina tasks.

[bwanglzu]

okay okay @Samoed didn't aware you're working on it, i can imaging because now i'm still testing the implementation (marked as draft). What should we do now? shall i take over jina models?

[bwanglzu]

btw the reason i add here is because i want to give a full MMTEB evaluation of jina models

[Samoed]

Yes, I wanted too. I will provide my tests results in an hour

[KennethEnevoldsen]

in #1316 we update the metadata for all models:

It might be nice to add:

    max_tokens=...,
    embed_dim=...,
    n_parameters=...,
    memory_usage=...,
    license="cc-by-nc-4.0",
    reference=..., # you will need to pull from the PR to add this
    similarity_fn_name="cosine",
    framework=[...],
    use_instuctions=...,

[bwanglzu]

clear

[bwanglzu]

@Samoed @KennethEnevoldsen i'll close my PR and focus on review and testing #1319 as it is already in a better state