[mieb] Any2TextMultipleChoice Abstask&Evaluator & four tasks in CV-bench #1287
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Adding:
the logic is first grabbing unique candidate choices from the task (e.g., the 788 questions in the count task only has 17 unique candidates), encode them, store in a {candidate: embedding} dict. In scoring time, we query the dict and do similarity matching. This gets rid of the need to repetitive encoding, and makes it easier for queries with different number of candidates that can't be supported by
AbsTaskImageTextPairClassification
atm.Checklist
make test
.make lint
.