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import gradio as gr | |
from translate import translator_fn | |
def predict(text): | |
result = translator_fn(text) | |
return { | |
"input_text": result.input_text, | |
"input_tokens": result.input_tokens, | |
"n_input": result.n_input, | |
"output_text": result.output_text, | |
"output_tokens": result.output_tokens, | |
"n_output": result.n_output, | |
"output_scores": result.output_scores, | |
"cross_attention": result.cross_attention.tolist(), | |
} | |
gradio_app = gr.Interface( | |
predict, | |
inputs=gr.Text(placeholder="Enter a sentence to translate...", label="Input text"), | |
outputs=[gr.Json(label="Model output")], | |
title="En2Ru Scientific Translator", | |
description="Translate scientific texts from English to Russian", | |
) | |
if __name__ == "__main__": | |
gradio_app.launch() | |