Colab update - fix classify

app.py

@@ -11,8 +11,7 @@ labels = dataset['train'].features['labels'].names
 
 def classify(im):
   features = feature_extractor(im, return_tensors='pt')
-  inp = model(**features)
-  logits = torch.nn.functional.softmax(inp.logits, dim=-1)
+  logits = model(features["pixel_values"])[-1]
   probability = torch.nn.functional.softmax(logits, dim=-1)
   probs = probability[0].detach().numpy()
   confidences = {label: float(probs[i]) for i, label in enumerate(labels)} 
@@ -22,7 +21,7 @@ def classify(im):
 interface = gr.Interface(
     title="Leaf Spot Classifier",
     description="Classify the leaf into one of: angular_leaf_spot, bean_rust, healthy",
-    examples="examples"
+    examples="examples",
     fn=classify,
     inputs=gr.Image(shape=(224, 224)),
     outputs=gr.Label(num_top_classes=3),