model: add kalm_models ModelMeta

[YanshekWoo]

Checklist

• I did not add a dataset, or if I did, I added the dataset checklist to the PR and completed it.
• I did not add a model, or if I did, I added the model checklist to the PR and completed it.

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.
• The model is public, i.e. is available either as an API or the wieght are publicly avaiable to download

[Samoed]

Can you add implementation of your model? If it similar to original KALM, I can push work on that PR

[YanshekWoo]

If it similar to original KALM, I can push work on that PR

Yes, it is almost the same implementation of HIT_TMG__KaLM_embedding_multilingual_mini_instruct_v1.

Perhaps the entire set of models related to KaLM should be moved to kalm_models.py.

[Samoed]

Yes, I will try to finish work on #2478 on weekends then

[Samoed]

@YanshekWoo can you try to run your models with implementation from #2478? It was merged to main

[YanshekWoo]

@Samoed OK, I will try to test it. Thanks.

[YanshekWoo]

@Samoed
I have tested the latest version of MTEB (1.38.30), and I believe its results are completely fine now.

Some of the results (from different task type) for HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5 are as follows:

Task	Reported	Reproduced
EmotionClassification	0.86900	0.86885
FiQA2018	0.44741	0.44072
SprintDuplicateQuestions	0.93057	0.930568
STS12	0.80167	0.801666

The code of evaluation is as follows:

import mteb

# Specify the model that we want to evaluate
model = mteb.get_model("HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5")

# specify what you want to evaluate it on
tasks = mteb.get_tasks(tasks=["EmotionClassification", "FiQA2018", "STS12", "SprintDuplicateQuestions"])

# run the evaluation
evaluation = mteb.MTEB(tasks=tasks)

results = evaluation.run(model,
            encode_kwargs={"batch_size": 256},
            verbosity=2,)

[YanshekWoo]

I have created a new PR via the latest mteb.
Please refer to the new one: #2850