re-search/DocProduct
Medical Q&A with Deep Language Models
Combines fine-tuned BioBERT encoders with FAISS vector search for retrieving relevant medical information, then conditions a fine-tuned GPT-2 generator on retrieved context to produce answers. Built on TensorFlow 2.0 and trained on 700,000+ medical Q&A pairs from Reddit, HealthTap, and WebMD, with embedding-space metric learning via feedforward network heads to align question and answer representations.
571 stars and 10 monthly downloads. No commits in the last 6 months. Available on PyPI.
Stars
571
Forks
157
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 25, 2023
Monthly downloads
10
Commits (30d)
0
Dependencies
14
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