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import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
# Load the grammar correction model and tokenizer
model_name = "hassaanik/grammar-correction-model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
# Function for grammar correction using the grammar correction model
def correct_grammar(text):
# Tokenize the input text
inputs = tokenizer.encode(text, return_tensors="pt", max_length=512, truncation=True)
# Generate the corrected output from the model
outputs = model.generate(inputs, max_length=512, num_beams=5, early_stopping=True)
# Decode the generated tokens to get the corrected text
corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
return corrected_text
# Gradio interface for the grammar correction app
interface = gr.Interface(
fn=correct_grammar,
inputs="text",
outputs="text",
title="Grammar Correction App",
description="Enter a sentence or paragraph to get grammar corrections using a Seq2Seq grammar correction model."
)
if __name__ == "__main__":
interface.launch()
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