from transformers import pipeline | |
import gradio as gr | |
# Load the desired model using Hugging Face's model hub | |
model = pipeline(model="philschmid/bart-large-cnn-samsum") | |
def generate_text(input_text): | |
# Set the maximum response size to 100 characters | |
output = model(input_text, max_length=100, do_sample=True) | |
# Access the generated response | |
response = output[0]['summarized_text'] | |
return response | |
iface = gr.Interface( | |
fn=generate_text, | |
inputs=gr.inputs.Textbox("Input Text"), | |
outputs="text", | |
title="Text Generation App", | |
description="Enter an input text and get a generated response (limited to 100 characters)." | |
) | |