File size: 1,210 Bytes
577164e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 |
from transformers import T5ForConditionalGeneration, T5Tokenizer
from utils.simple_bleu import simple_score
import torch
model_name = 'jbochi/madlad400-10b-mt'
model = T5ForConditionalGeneration.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
tokenizer = T5Tokenizer.from_pretrained(model_name)
def translate_ko2en(text):
text = f"<2en> {text}"
input_ids = tokenizer(text, return_tensors="pt").input_ids.to(model.device)
outputs = model.generate(input_ids=input_ids, max_new_tokens=2048)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
return result
def translate_en2ko(text):
text = f"<2ko> {text}"
input_ids = tokenizer(text, return_tensors="pt").input_ids.to(model.device)
outputs = model.generate(input_ids=input_ids, max_new_tokens=2048)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
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()
|