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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()
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