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import gradio as gr | |
from transformers import pipeline | |
# Load your fine-tuned model (ensure it's available in your Hugging Face model repository) | |
corrector = pipeline("text2text-generation", model="Pisethan/spelling-finetuned-model") | |
# Define the function for prediction | |
def correct_spelling(text): | |
result = corrector(text)[0]["generated_text"] | |
return result | |
# Create a Gradio interface | |
interface = gr.Interface(fn=correct_spelling, inputs="text", outputs="text", | |
title="Khmer Spelling Correction", | |
description="Enter Khmer text to correct spelling errors.") | |
# Launch the interface | |
interface.launch() | |