Create app.py

app.py

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+from transformers import pipeline
+
+# Simple text generation "Hello World" example
+def huggingface_hello_world():
+    # Use a pre-trained text generation model
+    generator = pipeline('text-generation', model='gpt2')
+    
+    # Generate a response to a "Hello" prompt
+    hello_response = generator("Hello, how are you today?", max_length=50, num_return_sequences=1)
+    
+    # Print the generated text
+    print("Model's Hello World Response:")
+    print(hello_response[0]['generated_text'])
+
+# Another example with text classification
+def huggingface_sentiment_hello():
+    # Use a sentiment analysis model
+    classifier = pipeline('sentiment-analysis')
+    
+    # Classify a "Hello World" sentiment
+    sentiment = classifier("Hello World! This is a nice day.")
+    
+    # Print the sentiment result
+    print("\nSentiment Analysis of 'Hello World':")
+    print(f"Sentiment: {sentiment[0]['label']}")
+    print(f"Confidence: {sentiment[0]['score']:.2f}")
+
+# Run the examples
+if __name__ == "__main__":
+    huggingface_hello_world()
+    huggingface_sentiment_hello()