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---
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))
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