PaliGemma Chest X-Ray Vision Model
Fine-tuned vision-language model for Portuguese chest X-ray report generation.
Model Details
- Base Model: google/medgemma-4b-it
- Task: Medical image report generation (image-text-to-text)
- Language: Portuguese (Brazilian)
- Fine-tuning Method: QLoRA (4-bit quantization)
Capabilities
This model can:
- Analyze chest X-ray images
- Generate structured radiology reports with TÉCNICA, ACHADOS, and IMPRESSÃO sections
- Identify common chest pathologies
Usage
from transformers import PaliGemmaProcessor, PaliGemmaForConditionalGeneration
from PIL import Image
processor = PaliGemmaProcessor.from_pretrained("MedeHealth/paligemma-chest-xray-vision")
model = PaliGemmaForConditionalGeneration.from_pretrained("MedeHealth/paligemma-chest-xray-vision")
image = Image.open("chest_xray.png")
prompt = "Analyze this chest X-ray and provide a structured radiology report."
inputs = processor(text=prompt, images=image, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=1024)
report = processor.decode(outputs[0], skip_special_tokens=True)
print(report)
Deployment
Deploy to HuggingFace Inference Endpoints with task type: image-text-to-text
Limitations
- For research and educational purposes
- Should not be used as sole basis for clinical decisions
- Requires radiologist review and validation
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