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import torch
from transformers import pipeline
from utils.simple_bleu import simple_score
pipe = pipeline("text-generation", model="Unbabel/TowerInstruct-v0.1", torch_dtype=torch.bfloat16, device_map="auto")
def translate_ko2en(text):
messages = [
{"role": "user", "content": f"Translate the following text from Korean into English.\n: Korean:{text}\nEnglish:"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=2048, do_sample=False)
result = outputs[0]["generated_text"]
result = result.split('<|im_start|>assistant')[1]
result = result.replace('\n:', '')
result = result.lstrip('\n')
result = result.lstrip(':')
return result
def translate_en2ko(text):
messages = [
{"role": "user",
"content": f"Translate the following text from English into Korean.\nEnglish: {text} \nKorean:"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=2048, do_sample=False)
result = outputs[0]["generated_text"]
result = result.split('<|im_start|>assistant')[1]
result = result.replace('\n:', '')
result = result.lstrip('\n')
result = result.lstrip(':')
return result
def main():
while True:
text = input('>')
en_text = translate_ko2en(text)
ko_text = translate_en2ko(en_text)
print('en_text', en_text)
print('ko_text', ko_text)
print('score', simple_score(text, ko_text))
if __name__ == "__main__":
main()
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