import mteb

meta = mteb.get_model_meta("minishlab/M2V_base_output")
model = meta.load_model()

task = mteb.get_task("LccSentimentClassification")
eval = mteb.MTEB(tasks=[task])
results = eval.run(model, overwrite_results=True, co2_tracker=False)


print(results[0].get_score())
# v1
# 0.35200000000000004

# v2
# 0.388


meta = mteb.get_model_meta("sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2")
model = meta.load_model()

task = mteb.get_task("LccSentimentClassification")
eval = mteb.MTEB(tasks=[task])
results = eval.run(model, overwrite_results=True, co2_tracker=False)
print(results[0].get_score())

# v1
# 0.5453333333333333

# v2
# 0.5673333333333332