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import gradio as gr
from transformers import AutoTokenizer, T5ForConditionalGeneration
# Load the CoEdIT-xl model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("grammarly/coedit-xl")
model = T5ForConditionalGeneration.from_pretrained("grammarly/coedit-xl")
def edit_text(input_text):
# Tokenize input text
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
# Generate edited text
outputs = model.generate(input_ids, max_length=256)
edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
return edited_text
# Create a Gradio interface
iface = gr.Interface(
fn=edit_text,
inputs=gr.Textbox(label="Enter a sentence to edit:"),
outputs=gr.Textbox(label="Edited sentence:"),
title="CoEdIT Text Editor",
description="Edit text using the CoEdIT-xl model.",
)
if __name__ == "__main__":
iface.launch()
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