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import random | |
import time | |
import gradio as gr | |
from transformers import pipeline | |
translator = pipeline("translation", model=f'Broomva/bart-large-translation-spa-guc') | |
def slow_echo(message, history): | |
translated = translator(message)[0]['translation_text'] | |
for i in range(len(translated)): | |
time.sleep(0.05) | |
yield translated[: i+1] | |
demo = gr.ChatInterface(slow_echo).queue() | |
if __name__ == "__main__": | |
demo.launch() |