BioGPT-BQF-TMK-Small

A fine-tuned BioGPT model for Boolean query formalization in biomedical systematic reviews, incorporating Titles, MeSH Terms, and Keywords to improve PubMed search query generation.

Model Overview

• Base Model: BioGPT
• Fine-tuned on: Semi-synthetic generated data
• Task: Boolean Query Generation for PubMed searches
• Inputs: Research topic title, MeSH terms, and Keywords
• Outputs: Optimized PubMed Boolean search query

Usage

from transformers import BioGptForCausalLM, BioGptTokenizer

model_name = "AI4BSLR/BioGPT-BQF-TMK-Small"
model = BioGptForCausalLM.from_pretrained(model_name)
tokenizer = BioGptTokenizer.from_pretrained(model_name)

input_text = "Title: Heterogeneity in Lung Cancer, MeSH: Biomarkers, Tumor, Genetic Heterogeneity, Keywords: Biomarkers, Query: "
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))