Update app.py

app.py

@@ -1,22 +1,29 @@
-from transformers import pipeline
 import gradio as gr
+from transformers import pipeline
+
+# Specify the model and revision explicitly
+model_name = "distilbert-base-uncased-finetuned-sst-2-english"
+revision = "af0f99b"
 
-# Load the sentiment analysis model
-sentiment_analysis = pipeline("sentiment-analysis")
+# Load the sentiment analysis pipeline with the specified model and revision
+sentiment_pipeline = pipeline("sentiment-analysis", model=model_name, revision=revision)
 
-# Define the prediction function
 def predict_sentiment(text):
-    result = sentiment_analysis(text)[0]
+    """
+    Predicts the sentiment of the input text.
+    Returns the label (POSITIVE/NEGATIVE) and the confidence score.
+    """
+    result = sentiment_pipeline(text)[0]
     label = result['label']
     confidence = round(result['score'], 4)
     return f"Sentiment: {label}, Confidence: {confidence}"
 
 # Create a Gradio interface
 interface = gr.Interface(fn=predict_sentiment,
-                         inputs=gr.inputs.Textbox(lines=2, placeholder="Type your text here..."),
+                         inputs=gr.inputs.Textbox(lines=2, placeholder="Enter Text Here..."),
                          outputs="text",
-                         title="Text Sentiment Analysis",
-                         description="This tool predicts the sentiment of the entered text. Sentiment can be positive, negative, or neutral.")
+                         title="Simple Text Sentiment Analysis",
+                         description="A simple text sentiment analysis tool using Hugging Face's transformers.")
 
 # Launch the application
 interface.launch()