---
tags:
- biogpt
- boolean-query
- biomedical
- systematic-review
- pubmed
license: unknown
model-index:
- name: BioGPT-BQF-TMK-Large
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: CLEF TAR
      type: biomedical
    metrics:
      - name: Precision @100
        type: precision
        value: 0.1455
      - name: Recall @1000
        type: recall
        value: 0.2661
---

# BioGPT-BQF-TMK-Large
Fine-tuned BioGPT for Biomedical Boolean Query Formalization using Titles only.

## Model Details
- Base Model: BioGPT
- Fine-tuned on: Semi-synthetic generated data
- Task: Boolean Query Generation for PubMed searches

## How to Use
```python
from transformers import BioGptForCausalLM, BioGptTokenizer

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

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))