Update app.py

app.py

@@ -1,24 +1,14 @@
 import gradio as gr
 import requests
 from datasets import load_dataset
-from transformers import AutoFeatureExtractor, AutoModelForImageClassification
-from transformers import ViTFeatureExtractor, ViTForImageClassification
 from PIL import Image
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
 import requests
-extractor = AutoFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
-model = AutoModelForImageClassification.from_pretrained("google/vit-base-patch16-224")
-
 dataset = load_dataset("hamdan07/UltraSound-lung")
-image = Image.open(requests.get(dataset, stream=True).raw)
-feature_extractor = ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224')
-model = ViTForImageClassification.from_pretrained('google/vit-base-patch16-224')
-inputs = feature_extractor(images=image, return_tensors="pt")
-outputs = model(**inputs)
-logits = outputs.logits
-predicted_class_idx = logits.argmax(-1).item()
-print("Predicted class:", model.config.id2label[predicted_class_idx])
 API_URL = "https://api-inference.huggingface.co/models/hamdan07/UltraSound-Lung"
 headers = {"Authorization": "Bearer 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"}
+extractor = AutoFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
+model = AutoModelForImageClassification.from_pretrained("google/vit-base-patch16-224")
 
 def query(filename):
     with open(filename, "rb") as f: