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