Update app.py

app.py

@@ -1,20 +1,22 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the model locally (assuming model files are in this folder)
-classifier = pipeline("text-classification", model="./models/bert-base-goemotions-ekman", return_all_scores=True)
+classifier = pipeline(
+    "text-classification",
+    model="bhadresh-savani/bert-base-goemotions-ekman",
+    return_all_scores=True
+)
 
 def detect_emotions(text):
     results = classifier(text)[0]
-    sorted_results = sorted(results, key=lambda x: x["score"], reverse=True)
-    return {r['label']: round(r['score'], 3) for r in sorted_results}
+    return {r['label']: round(r['score'], 3) for r in sorted(results, key=lambda x: x["score"], reverse=True)}
 
 demo = gr.Interface(
     fn=detect_emotions,
     inputs=gr.Textbox(lines=4, placeholder="Enter a tweet or comment..."),
     outputs="label",
     title="Emotion Detection with BERT (GoEmotions)",
-    description="Detect joy, sadness, anger, and other emotions from text using a BERT-based model fine-tuned on the GoEmotions dataset."
+    description="Detect joy, sadness, anger, and more using BERT trained on GoEmotions."
 )
 
 demo.launch()