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import gradio as gr | |
from transformers import pipeline | |
pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ber") | |
def predict(text): | |
return pipe(text)[0]["translation_text"] | |
demo = gr.Interface( | |
fn=predict, | |
inputs='text', | |
outputs='text', | |
) | |
demo.launch() |