DDI Triage LoRA — amank-root/demo-ddi-1.5b-lora

LoRA adapter fine-tuned on the OpenEnv-DDI drug-drug interaction triage task.

Base model: Qwen/Qwen2.5-1.5B-Instruct
Task: Given a patient's medication list and labs, flag/monitor/ignore DDIs and suggest safer alternatives.
Training: 2 500 SFT rows (18 real + 480 synthetic cases), 2 epochs, r=8 LoRA.

Load

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct", torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("amank-root/demo-ddi-1.5b-lora")
model = PeftModel.from_pretrained(base, "amank-root/demo-ddi-1.5b-lora")
model = model.merge_and_unload()  # optional: merge for faster inference

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Model tree for amank-root/demo-ddi-1.5b-lora

Base model

Qwen/Qwen2.5-1.5B

Finetuned

Qwen/Qwen2.5-1.5B-Instruct

Adapter

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