[v2] Merge main #2412
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[v2] Merge main #2412
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* fix: Ensure BrightRetrieval is valid to run Not sure this is the best way to fix this. Let me know if you can find a better fix. fixes #2327 * fix: convert brightretrieval to two tasks * fix collecting error
* pass task name to all tasks * add test * fix loader
* fix: renaming Zeroshot -> ZeroShot Adresses #2078 * rename 1 * rename 2 * format * fixed error
Update AmazonPolarityClassification.py
… covid related scientific papers (#2302) * Clustrec covid new dataset and task * fix * fix * fix * fix * fix * descriptive stats * change all mentions of clustrec-covidp2p to clustrec-covid * change ' to "
* fix: renaming Zeroshot -> ZeroShot Adresses #2078 * fix: minor style changes Adresses #2078 * fix: Major updates to documentation This PR does the following: - This introduced other modalities more clearly in the documentation as well as make it easier to transition to a full on documentation site later. - added minor code updates due to discovered inconsistencies in docs and code. - Added the MMTEB citation where applicable - makes the docs ready to move torchvision to an optional dependency * Moved VISTA example * rename 1 * rename 2 * format * fixed error * fix: make torchvision optional (#2399) * fix: make torchvision optional * format * add docs * minor fix * remove transform from Any2TextMultipleChoiceEvaluator --------- Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * move Running SentenceTransformer model with prompts to usage --------- Co-authored-by: Isaac Chung <chungisaac1217@gmail.com>
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Code Quality
make lintto maintain consistent style.Documentation
Testing
make test-with-coverage.make testormake test-with-coverageto ensure no existing functionality is broken.Adding datasets checklist
Reason for dataset addition: ...
mteb -m {model_name} -t {task_name}command.sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2intfloat/multilingual-e5-smallself.stratified_subsampling() under dataset_transform()make test.make lint.Adding a model checklist
mteb.get_model(model_name, revision)andmteb.get_model_meta(model_name, revision)