Update app.py

app.py

@@ -1,27 +1,24 @@
-
-from transformers import pipeline,AutoTokenizer, AutoModelForSequenceClassification
-import gradio as gr
-
-
-pipe = pipeline("text-classification", model="Taraassss/sentiment_analysis_IT")
-tokenizer = AutoTokenizer.from_pretrained("Taraassss/sentiment_analysis_IT")
-model = AutoModelForSequenceClassification.from_pretrained("Taraassss/sentiment_analysis_IT")
-
-
-pipe = pipeline("text-classification", model="Taraassss/sentiment_analysis_IT")
-
-def sentiment_analysis(text):
-    result = pipe(text) 
-    sentiment = result[0]['label']  
-    score = result[0]['score']  
-    return f"Sentiment: {sentiment}, Confidence: {score:.2f}"
-
-iface = gr.Interface(
-    fn=sentiment_analysis, 
-    inputs=gr.Textbox(lines=2, placeholder="Inserisci il testo da analizzare..."),  
-    outputs="text",  
-    title="Analisi del Sentimento Italiano",
-    description="Inserisci una frase in italiano per analizzare il sentimento.",
-)
-
-iface.launch()
+
+from transformers import pipeline,AutoTokenizer, AutoModelForSequenceClassification
+import gradio as gr
+
+
+pipe = pipeline("text-classification", model="Taraassss/sentiment_analysis_IT")
+
+
+
+def sentiment_analysis(text):
+    result = pipe(text) 
+    sentiment = result[0]['label']  
+    score = result[0]['score']  
+    return f"Sentiment: {sentiment}, Confidence: {score:.2f}"
+
+iface = gr.Interface(
+    fn=sentiment_analysis, 
+    inputs=gr.Textbox(lines=2, placeholder="Inserisci il testo da analizzare..."),  
+    outputs="text",  
+    title="Analisi del Sentimento Italiano",
+    description="Inserisci una frase in italiano per analizzare il sentimento.",
+)
+
+iface.launch()