first one

app.py

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+import gradio as gr
+from transformers import pipeline
+
+sentiment_pipeline= pipeline("sentiment-analysis", model="cardiffnlp/twitter-roberta-base-sentiment")
+
+
+# texts = ["Hugging face? weired, but memorable.", "I am despirate"]
+
+# results = sentiment_pipeline(texts)
+
+# for text, results in zip(texts, results):
+    # print(f"Text: {text}")
+    # print(f"Sentiment: {result['label']}, Score: {result['score']:.4f}\n")
+  
+    
+def predict_sentiment(text):
+    result = sentiment_pipeline(text)
+    return result[0]['label'], result[0]['score']
+
+iface = gr.Interface(fn=predict_sentiment, inputs="text", outputs = ["label","number"])
+
+if __name__ == "__main__": 
+    iface.launch()
+