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Sepideh2027/PathogenAgentAI-BioGPT-LoRA
PathogenAgentAI-BioGPT-LoRA is a machine learning model from Sepideh2027. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
Year: 2024–2025 License: MIT Author: Sepideh Moafi
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From the Hugging Face model README
Year: 2024–2025
License: MIT
Author: Sepideh Moafi
A parameter-efficient LoRA adapter for BioGPT, developed as part of the PathogenAgentAI research software project. Fine-tuned on ClinVar-derived instruction data for biomedical language-model applications.
Not intended for clinical diagnosis, treatment decisions, or direct clinical use.
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("microsoft/biogpt")
model = PeftModel.from_pretrained(base_model, "Sepideh2027/PathogenAgentAI-BioGPT-LoRA")
Training Details
· Training data: ~20,000 ClinVar-derived instruction-style examples (16k/2k/2k train/validation/test split)
· Training procedure: LoRA, BF16 mixed precision
· Hardware: NVIDIA T4 GPU
Limitations
· Inherits all limitations of the base BioGPT model.
· Not validated for clinical use.
· Generated outputs should be independently verified against authoritative biomedical sources.
Related Resources
· Fine-tuned model: Sepideh2027/biogpt-clinvar-finetuned
· Instruction-tuning dataset: Sepideh2027/Agent
Citation
@software{Moafi2025pathogenagent,
author = {Moafi, Sepideh},
title = {PathogenAgentAI-BioGPT LoRA Adapter},
year = {2025},
url = {https://huggingface.co/Sepideh2027/PathogenAgentAI-BioGPT-LoRA}
}
BioGPT-ClinVar: Parameter-Efficient Fine-Tuning of a Biomedical Foundation Model. Research Square, 2026. DOI: 10.21203/rs.3.rs-10196893/v1
Contact
Sepideh Moafi
GitHub: AIResearcher20
Hugging Face: Sepideh2027