Create App.py

App.py

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+from transformers import pipeline
+import torch
+import gradio as gr
+
+# Initialize zero-shot classification pipeline
+classifier = pipeline("zero-shot-classification",
+                                      model="MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7",
+                                      device=0 if torch.cuda.is_available() else -1)
+
+def classify_text(text, labels):
+                   # Split labels into a list
+                   candidate_labels = [label.strip() for label in labels.split(",")]
+    
+                   # Perform zero-shot classification
+                   result = classifier(text, candidate_labels, multi_label=False)
+    
+                   # Format output
+                   output = ""
+                   for label, score in zip(result['labels'], result['scores']):
+                       percentage = score * 100
+                       output += f"{label}: {percentage:.2f}%\n"
+    
+                   return output
+
+# Create Gradio interface
+iface = gr.Interface(
+                   fn=classify_text,
+                   inputs=[
+                       gr.Textbox(label="Enter text to classify", lines=3),
+                       gr.Textbox(label="Enter labels (comma-separated)", value="politics, sports, technology, entertainment")
+                   ],
+                   outputs=gr.Textbox(label="Classification Results"),
+                   title="Zero-Shot Text Classification",
+                   description="Enter text and labels to classify the text into different categories."
+)
+
+# Launch the app
+iface.launch()