MedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions. MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length of 12.77 and high topical diversity.
Each sample contains a question, correct answer(s), and other options which require a deeper language understanding as it tests the 10+ reasoning abilities of a model across a wide range of medical subjects & topics. A detailed explanation of the solution, along with the above information, is provided in this study.
See the original resource from: https://huggingface.co/datasets/openlifescienceai/medmcqa
# Search
curl -X POST "https://search.dria.co/hnsw/search" \
-H "x-api-key: <YOUR_API_KEY>" \
-H "Content-Type: application/json" \
-d '{"rerank": true, "top_n": 10, "contract_id": "5KNcQ-phrxlJlKmHR4RYxEtJglR79-d7coRbA0HqTK0", "query": "What is alexanDRIA library?"}'
# Query
curl -X POST "https://search.dria.co/hnsw/query" \
-H "x-api-key: <YOUR_API_KEY>" \
-H "Content-Type: application/json" \
-d '{"vector": [0.123, 0.5236], "top_n": 10, "contract_id": "5KNcQ-phrxlJlKmHR4RYxEtJglR79-d7coRbA0HqTK0", "level": 2}'