app.py

from transformers import pipeline

# Load the model
model_name = "soufyane/gemma_data_science"
text_generator = pipeline("text-generation", model=model_name)

def process_text_gemma(input_text):
    # Generate text using the model
    response = text_generator(f"question: {input_text}", max_length=256)[0]['generated_text']
    return response

def main(input_text):
    return process_text_gemma(input_text[0])

import gradio as gr

gr.Interface(
    fn=main,
    inputs=["text"],
    outputs=["text"],
    title="Gemma Data Science Model",
    description="This is a text-to-text model for data science tasks.",
    live=True
).launch()