Create app.py

app.py

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+from transformers import pipeline
+import gradio as gr
+
+# Load the text generation pipeline
+pipe = pipeline("text-generation", model="google/gemma-2-2b-jpn-it")
+
+def generate_text(messages):
+    # Extracting the content from the messages
+    user_message = messages["content"]
+    
+    # Using the pipeline to generate a response
+    result = pipe(user_message, max_length=50, num_return_sequences=1)
+    
+    # Return the generated text
+    return result[0]["generated_text"]
+
+# Set up Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Text Generation with Hugging Face's gemma-2-2b-jpn-it")
+    
+    # Input for user's message
+    user_input = gr.Textbox(label="Your Message", placeholder="Type a message", value="Who are you?")
+    
+    # Output for generated response
+    output_text = gr.Textbox(label="Generated Response")
+    
+    # Button to trigger text generation
+    generate_button = gr.Button("Generate Response")
+    
+    # Link button click with text generation function
+    generate_button.click(fn=generate_text, inputs={"content": user_input}, outputs=output_text)
+
+# Launch the Gradio app
+demo.launch()