Update app.py

app.py

@@ -1,13 +1,8 @@
 from transformers import pipeline
 from PIL import Image
 
-#device = torch.device("cpu")
-
-#processor = EfficientNetImageProcessor.from_pretrained("models/dennisjooo/Birds-Classifier-EfficientNetB2")
-#model = EfficientNetForImageClassification.from_pretrained("models/dennisjooo/Birds-Classifier-EfficientNetB2").to(device)
-
 def predict(image):
-    pipe = pipeline("image-classification", model="models/dennisjooo/Birds-Classifier-EfficientNetB2")
+    pipe = pipeline("image-classification", model="dennisjooo/Birds-Classifier-EfficientNetB2")
     predictions = pipe(img)
     return {p["label"]: p["score"] for p in predictions}