Update app.py

app.py

@@ -1,22 +1,12 @@
-import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 from transformers import pipeline
 
-# Load pre-trained sentiment analysis model
-sentiment_model = pipeline("sentiment-analysis")
+# Load a multi-class sentiment model
+model_name = "cardiffnlp/twitter-roberta-base-sentiment"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+sentiment_model = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
 
-# Define function to use the model
 def analyze_sentiment(text):
     result = sentiment_model(text)[0]
     return f"Label: {result['label']} | Confidence: {result['score']:.2f}"
-
-# Create Gradio interface
-demo = gr.Interface(
-    fn=analyze_sentiment,
-    inputs=gr.Textbox(lines=3, placeholder="Type a sentence here..."),
-    outputs="text",
-    title="Simple Sentiment Analyzer",
-    description="Find out if your text is Positive or Negative using a BERT model."
-)
-
-# Launch the app
-demo.launch()