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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
import gradio as grad
model_name = "Helsinki-NLP/opus-mt-ko-en"
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
#opus_translator = pipeline("translation", model=model_name)
def translate(text):
inputs = tokenizer(text, return_tensors="pt")
translation_output = model.generate(**input)
response = tokenizer.decode(translation_output[0], skip_special_tokens=True)
#response = opus_translator(text)
return response
# Web UI
grad.Interface(translate, inputs=["text"], outputs=["text"]).launch()
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