Create app.py

app.py

@@ -0,0 +1,67 @@
+from transformers import pipeline
+import gradio as gr
+
+# Initialize text classification pipeline
+classifier = pipeline("text-classification", model="facebook/bart-large-mnli")
+
+def classify_text(text):
+    if not text.strip():
+        return "Please enter some text to classify"
+    
+    try:
+        # Get classification results
+        results = classifier(text)
+        
+        # Format results
+        output = "## Classification Results:\n\n"
+        for result in results:
+            label = result['label']
+            score = result['score'] * 100
+            output += f"- **{label}**: {score:.2f}%\n"
+        
+        return output
+    except Exception as e:
+        return f"Error during classification: {str(e)}"
+
+# Gradio interface
+with gr.Blocks(title="Text Classifier") as demo:
+    gr.Markdown("# 📝 Text Classification AI")
+    gr.Markdown("Classify text using Hugging Face's BART model")
+    
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                lines=8,
+                placeholder="Enter text to classify...",
+                label="Input Text"
+            )
+            classify_btn = gr.Button("Classify Text", variant="primary")
+            
+        with gr.Column():
+            output_text = gr.Markdown(label="Classification Results")
+    
+    classify_btn.click(
+        classify_text,
+        inputs=input_text,
+        outputs=output_text
+    )
+    
+    gr.Examples(
+        [
+            ["I love this movie, it's fantastic!"],
+            ["This product is terrible and broke after one day"],
+            ["The weather today is sunny and warm"],
+            ["Machine learning is a subset of artificial intelligence"],
+            ["I'm feeling sad and disappointed about the results"]
+        ],
+        inputs=input_text
+    )
+    
+    gr.Markdown("### About This Model")
+    gr.Markdown("- **Model**: [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli)")
+    gr.Markdown("- **Task**: Zero-shot text classification")
+    gr.Markdown("- **Capabilities**: Classifies text into various categories without specific training")
+    gr.Markdown("- **Note**: First classification may take 10-15 seconds (model loading)")
+
+if __name__ == "__main__":
+    demo.launch()