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import gradio as gr
from transformers import pipeline
# Load the translation pipeline
pipe = pipeline("translation", model="facebook/nllb-200-distilled-600M")
# Define the translation function
def translate_text(text, source_language, target_language, max_length=200):
# Define source and target languages (e.g., 'eng_Latn' -> 'fra_Latn')
language_pair = f"{source_language}-{target_language}"
response = pipe(
text,
src_lang=source_language,
tgt_lang=target_language,
max_length=max_length
)
return response[0]['translation_text']
# Create the Gradio app interface
with gr.Blocks() as app:
gr.Markdown("## Translation App")
gr.Markdown(
"Enter text in the source language, and the model will translate it to the target language. "
"This app uses the `facebook/nllb-200-distilled-600M` model."
)
gr.Markdown("### To choose the languages: [https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200](https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200)")
with gr.Row():
input_text = gr.Textbox(
label="Input Text",
placeholder="Type the text to translate...",
lines=4
)
output_translation = gr.Textbox(label="Translated Text", lines=4)
with gr.Row():
source_language = gr.Textbox(
label="Source Language Code",
placeholder="e.g., eng_Latn (for English)"
)
target_language = gr.Textbox(
label="Target Language Code",
placeholder="e.g., fra_Latn (for French)"
)
max_length = gr.Slider(
label="Max Length",
minimum=50,
maximum=500,
step=50,
value=200
)
submit_button = gr.Button("Translate")
submit_button.click(
fn=translate_text,
inputs=[input_text, source_language, target_language, max_length],
outputs=output_translation
)
# Launch the app
if __name__ == "__main__":
app.launch()
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