Bio-gpt-oss-20B
Collection
Bio-GPT-OSS-20B: Fine-tuning Large Language
Models for Biomedical Question Answering with
Reasoning
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1 item
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Updated
A specialized biomedical question-answering model fine-tuned from gpt-oss-20B on scholarly Q&A extraction tasks from biomedical research papers.
The model was trained on ~ 1000 conversation pairs extracted from biomedical research papers, featuring:
{
"paper_id": "PMC8026465",
"reasoning_language": "English",
"developer": "You are a scholarly Q & A extraction agent. Only use the provided paper. Be concise and precise.",
"user": "According to the comparative analysis by Wu et al., how do the kidney organoid differentiation protocols compare?",
"analysis": "Steps:\n1) Locate the section \"3D kidney organoids\"...\n2) Find Wu et al. comparative study...",
"final": "According to Wu et al., both Morizane and Takasato protocols generated immature tissue, expressing ~20% of adult transcription factors.",
"messages": [
{"role": "system", "content": "...", "thinking": null},
{"role": "user", "content": "...", "thinking": null},
{"role": "assistant", "content": "...", "thinking": "Steps:\n1) Locate..."}
]
}
Question: Kidney organoid protocol comparison Analysis: Multi-step evidence extraction from specific paper sections Answer: Quantitative comparison with statistical details (both protocols ~20% maturity)
Question: Cognitive test predictive ability differences
Analysis: Statistical result extraction and comparison across test conditions
Answer: 1-week test superior predictive power (p=.003 vs p=.11)
@model{bio-gpt-oss-20b,
title={Bio-GPT-OSS-20B: Biomedical Question Answering with Reasoning},
author={Your Name},
year={2024},
base_model={gpt-oss-20B}
}
This gpt_oss model was trained 2x faster with Unsloth and Huggingface's TRL library.
Base model
openai/gpt-oss-20b