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omaraboelmaaty/llava-med-lora-v2
llava-med-lora-v2 is a machine learning model from omaraboelmaaty. 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.
Fine-tuned LoRA adapter for microsoft/llava-med-v1.5-mistral-7b, specialized in generating structured radiology reports from medical scans (X-ray, CT, MRI).
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Updated Jul 7, 2026
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From the Hugging Face model README
Fine-tuned LoRA adapter for microsoft/llava-med-v1.5-mistral-7b, specialized in generating structured radiology reports from medical scans (X-ray, CT, MRI).
| Property | Value |
|---|---|
| Base Model | microsoft/llava-med-v1.5-mistral-7b |
| Fine-tune Method | QLoRA (LoRA rank 16) |
| Training Epochs | 2 |
| Learning Rate | 5e-5 |
| Best Val Loss | 0.907 |
| Languages | English / Arabic UI |
from peft import PeftModel
from llava.model.builder import load_pretrained_model
from llava.mm_utils import get_model_name_from_path
base_id = "microsoft/llava-med-v1.5-mistral-7b"
lora_id = "YOUR_USERNAME/llava-med-lora-v2"
name = get_model_name_from_path(base_id)
tokenizer, base, image_processor, _ = load_pretrained_model(
model_path=base_id, model_base=None,
model_name=name, load_4bit=True,
device_map="auto"
)
model = PeftModel.from_pretrained(base, lora_id, autocast_adapter_dtype=False)
model.eval()
Fine-tuned on curated medical imaging datasets including radiology reports paired with scan images.
@misc{llava-med-lora-v2,
title={LLaVA-Med LoRA v2 - Radiology Fine-tune},
year={2025},
publisher={Hugging Face}
}
This model is intended for research purposes only and should not be used as a substitute for professional medical advice, diagnosis, or treatment.