import gradio as gr | |
from transformers import pipeline | |
# Load the model | |
pipe = pipeline("summarization", model="prithivMLmods/t5-Flan-Prompt-Enhance") | |
def summarize_text(text): | |
result = pipe(text, max_length=150, min_length=30, do_sample=False) | |
return result[0]['summary_text'] | |
demo = gr.Interface(fn=summarize_text, inputs="text", outputs="text") | |
demo.launch() | |