Fix pipeline type to token-classification for NER model

app.py

@@ -10,10 +10,17 @@ import gradio as gr
 from transformers import pipeline
 
 # Load model from Hugging Face Hub
-classifier = pipeline("text-classification", model="Mhammad2023/bert-finetuned-ner", from_tf=True)
+classifier = pipeline("token-classification", model="Mhammad2023/bert-finetuned-ner", from_tf=True)
 
 def predict(text):
-    result = classifier(text)[0]
-    return f"{result['label']} ({round(result['score']*100, 2)}%)"
+    results = classifier(text)
+    if not results:
+        return "No entities found"
+    
+    output = []
+    for entity in results:
+        output.append(f"{entity['word']}: {entity['entity']} ({round(entity['score']*100, 2)}%)")
+    
+    return "\n".join(output)
 
-gr.Interface(fn=predict, inputs="text", outputs="text", title="Text Classification").launch()
+gr.Interface(fn=predict, inputs="text", outputs="text", title="Named Entity Recognition").launch()