Update app.py

app.py

@@ -1,72 +1,3 @@
-import gradio as gr
-from transformers import pipeline
-import torch
-
-# Initialize the zero-shot classification pipeline
-try:
-    classifier = pipeline(
-        "zero-shot-classification",
-        model="models/tasksource/ModernBERT-nli",
-        device=0 if torch.cuda.is_available() else -1
-    )
-except Exception as e:
-    print(f"Error loading model: {e}")
-    classifier = None
-
-def classify_text(text, candidate_labels):
-    """
-    Perform zero-shot classification on input text.
-    
-    Args:
-        text (str): Input text to classify
-        candidate_labels (str): Comma-separated string of possible labels
-    
-    Returns:
-        dict: Dictionary with labels as keys and confidence scores as values
-    """
-    if classifier is None:
-        # Return default response when model fails to load
-        return {"error": 1.0}
-    
-    try:
-        # Convert comma-separated string to list
-        labels = [label.strip() for label in candidate_labels.split(",")]
-        
-        # Perform classification
-        result = classifier(text, labels)
-        
-        # Convert to dictionary format that Gradio Label expects
-        return {label: float(score) for label, score in zip(result["labels"], result["scores"])}
-    
-    except Exception as e:
-        print(f"Classification error: {e}")
-        return {"error": 1.0}
 
-# Create Gradio interface
-iface = gr.Interface(
-    fn=classify_text,
-    inputs=[
-        gr.Textbox(
-            label="Text to classify",
-            placeholder="Enter text here...",
-            value="all cats are blue"
-        ),
-        gr.Textbox(
-            label="Possible labels (comma-separated)",
-            placeholder="Enter labels...",
-            value="true,false"
-        )
-    ],
-    outputs=gr.Label(label="Classification Results"),
-    title="Zero-Shot Text Classification",
-    description="Classify text into given categories without any training examples.",
-    examples=[
-        ["all cats are blue", "true,false"],
-        ["the sky is above us", "true,false"],
-        ["birds can fly", "true,false,unknown"]
-    ]
-)
-
-# Launch the app
-if __name__ == "__main__":
-    iface.launch(share=True)
+import gradio as gr
+gr.Interface.load("models/tasksource/ModernBERT-base-nli").launch()