Update app.py

app.py

@@ -1,10 +1,15 @@
-from transformers import pipeline
+from huggingface_hub import from_pretrained_fastai
 import gradio as gr
 
-classifier = pipeline("text-classification", model="yejimene/clasificadorTexto") 
+repo_id = "yejimene/clasificadorTexto"
+learner = from_pretrained_fastai(repo_id)
 
 def predict(text):
-    result = classifier(text)[0]
-    return {result['label']: result['score']}
-    
-gr.Interface(fn=predict, inputs="text", outputs=gr.outputs.Label()).launch(share=False)
+    pred,pred_idx,probs = learner.predict(text)
+    if pred == "0":
+        return "NEGATIVE"
+    elif pred == "1":
+        return "POSITIVE"
+    else:
+        return "error"
+gr.Interface(fn=predict, inputs="text", outputs="label", examples=["This movie was terrible and boring.","I loved this movie, it was amazing!"]).launch()