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from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr
# Load the model and tokenizer
model_path = '.' # Path to the current directory where files are located
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
summarizer = pipeline('summarization', model=model, tokenizer=tokenizer)
def summarize_text(text):
result = summarizer(text, max_length=150, min_length=30, do_sample=False)
return result[0]['summary_text']
gr_interface = gr.Interface(
fn=summarize_text,
inputs=gr.Textbox(lines=5, placeholder="Enter text to summarize here..."),
outputs=gr.Textbox(),
title="Text Summarization with Fine-Tuned Model",
description="Enter text to generate a summary using the fine-tuned summarization model."
)
if __name__ == "__main__":
gr_interface.launch(share=True)
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