aded distilbert interface

app.py

@@ -1,11 +1,26 @@
 import gradio as gr
-from setfit import SetFitModel
+from transformers import pipeline
 
-def greet(text):
-    model = SetFitModel.from_pretrained("skylord/setfit-bge-small-v1.5-sst2-8-shot-talk2loop") # Load from the Hugging Face Hub
-    preds = model.predict([text])
+# Load the sentiment analysis pipeline with DistilBERT
+distilbert_pipeline = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
 
-    return "Tag: " + preds 
+def predict_sentiment(text):
+    """
+    Predicts the sentiment of the input text using DistilBERT.
+    :param text: str, input text to analyze.
+    :return: str, predicted sentiment and confidence score.
+    """
+    result = distilbert_pipeline(text)[0]
+    label = result['label']
+    score = result['score']
+    return f"Sentiment: {label}, Confidence: {score:.2f}"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+# Create a Gradio interface
+iface = gr.Interface(fn=predict_sentiment,
+                     inputs=gr.inputs.Textbox(lines=2, placeholder="Type your text here..."),
+                     outputs="text",
+                     title="Sentiment Analysis with DistilBERT",
+                     description="This model predicts the sentiment of the input text. Enter a sentence to see if it's positive or negative.")
+
+# Launch the interface
+iface.launch()