Update app.py

app.py

@@ -1,20 +1,27 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
 from transformers import pipeline
-import torch
-
-
-# Load your model
-classifier = pipeline("text-classification", model="YonasMersha/fine-tuned-distilbert-emotion", tokenizer='YonasMersha/fine_tuned_distilbert_emotion')
 
+# Load the model and tokenizer from the same repository
+classifier = pipeline(
+    "text-classification",
+    model="YonasMersha/fine-tuned-distilbert-emotion",
+    tokenizer="YonasMersha/fine-tuned-distilbert-emotion"
+)
 
 # Define the prediction function
 def classify(text):
-    return classifier(text)[0]["label"]
+    result = classifier(text)[0]
+    return result["label"]
 
-# Create the interface
-iface = gr.Interface(fn=classify, inputs="text", outputs="label")
-iface.launch()
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=classify,
+    inputs=gr.Textbox(label="Enter a sentence", placeholder="e.g., I love this!"),
+    outputs=gr.Label(label="Predicted Emotion"),
+    title="Emotion Classifier",
+    description="Enter a sentence to classify its emotion (e.g., joy, sadness, anger)."
+)
 
+# Launch the interface
 if __name__ == "__main__":
-    demo.launch()
+    iface.launch()