Create app.py

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+from transformers import pipeline
+
+Sentiment pipeline
+sentiment = pipeline("text-classification", model="tabularisai/multilingual-sentiment-analysis")
+
+"""
+For more information on huggingface_hub Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
+
+def get_sentiment(text):
+  output = sentiment(text)
+  return f'The sentence was classified as "{output[0]["label"]}" with {output[0]["score"]*100}% confidence'
+
+
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+
+title = "Get a sentiment on you text"
+description = """
+The bot was takes your text and classify it as either 'Positive' or 'Negative'
+"""
+
+demo = gr.Interface(
+    fn=get_sentiment,
+    inputs="text",
+    outputs="text",
+    title=title,
+    description=description,
+    examples=[["I really enjoyed my stay !"], ["Worst rental I ever got"]],
+)
+
+
+if name == "main":
+    demo.launch()