Create app.py

app.py

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+from transformers import pipeline
+import gradio as gr
+
+# Load the text-to-text generation pipeline using the FLAN-T5 model
+pipe = pipeline("text2text-generation", model="google/flan-t5-large")
+
+# Function to generate text based on user input
+def generate_text(input_text):
+    # Generate output text using the pipeline
+    generated = pipe(input_text)
+    return generated[0]['generated_text']
+
+# Set up the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Text Generation using FLAN-T5 (google/flan-t5-large)")
+
+    # Input for user to provide text
+    text_input = gr.Textbox(label="Enter Text Prompt", placeholder="Type your prompt here...", value="Translate English to French: 'Hello, how are you?'")
+    
+    # Output to display the generated text
+    output_text = gr.Textbox(label="Generated Text", interactive=False)
+
+    # Button to trigger text generation
+    generate_button = gr.Button("Generate Text")
+
+    # Link button click to text generation function
+    generate_button.click(fn=generate_text, inputs=text_input, outputs=output_text)
+
+# Launch the Gradio app
+demo.launch()