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import gradio as gr
from transformers import pipeline
# Load the translation model
translator = pipeline("translation_en_to_hi", model="Helsinki-NLP/opus-mt-en-hi")
# Define the translation function
def translate_text(text):
if not text:
return "β οΈ Please provide some input text."
result = translator(text)[0]["translation_text"]
return result
# Create the Gradio interface
iface = gr.Interface(
fn=translate_text,
inputs=gr.Textbox(label="Enter English Text"),
outputs=gr.Textbox(label="Hindi Translation"),
title="English to Hindi Translator",
description="Enter English text to translate it into Hindi using a HuggingFace transformer model."
)
# π Launch with API enabled so external clients like Discord can POST data
iface.launch()
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