Update README.md

README.md

@@ -40,7 +40,7 @@ processor = CLIPProcessor.from_pretrained("flaviagiammarino/pubmed-clip-vit-base
 url = "https://d168r5mdg5gtkq.cloudfront.net/medpix/img/full/synpic9078.jpg"
 image = Image.open(requests.get(url, stream=True).raw)
 
-inputs = processor(text=["Chest X-Ray", "Brain MRI", "Abdominal CT Scan"], images=image, return_tensors="pt", padding=True)
+inputs = processor(text=["Chest X-Ray", "Brain MRI", "Abdomen CT Scan"], images=image, return_tensors="pt", padding=True)
 outputs = model(**inputs)
 logits_per_image = outputs.logits_per_image # this is the image-text similarity score
 probs = logits_per_image.softmax(dim=1) # we can take the softmax to get the label probabilities