| import gradio as gr | |
| from transformers import pipeline, set_seed | |
| # Load the h2oai/h2ogpt-oasst1-512-20b model from Hugging Face | |
| generator = pipeline('text-generation', model='h2oai/h2ogpt-oasst1-512-20b', device=0) | |
| # Set the seed for the model to ensure consistent results | |
| set_seed(42) | |
| # Define the chatbot function | |
| def chatbot(input_text): | |
| # Generate a response from the model given the input text | |
| output_text = generator(input_text, max_length=100)[0]['generated_text'] | |
| # Return the generated response | |
| return output_text.strip() | |
| # Create a Gradio interface for the chatbot | |
| interface = gr.Interface( | |
| fn=chatbot, | |
| inputs=gr.inputs.Textbox(lines=2, label="Input Text"), | |
| outputs=gr.outputs.Textbox(label="Generated Text") | |
| ) | |
| # Launch the interface | |
| interface.launch() | |