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Helsinki-NLP

https://hf-mirror.com/Helsinki-NLP/opus-mt-zh-en

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torchmodel = AutoModelForSeq2SeqLM.from_pretrained("/data/models/Helsinki-NLP/opus-mt-zh-en").eval()
tokenizer = AutoTokenizer.from_pretrained("/data/models/Helsinki-NLP/opus-mt-zh-en")def translate(text):with torch.no_grad():encoded = tokenizer([text], return_tensors="pt")sequences = model.generate(**encoded)return tokenizer.batch_decode(sequences, skip_special_tokens=True)[0]input = "青春不能回头，所以青春没有终点。,.,/'[' ——《火影忍者》"
print(translate(input))

from transformers import AutoModelForSeq2SeqLM, AutoTokenizertokenizer = AutoTokenizer.from_pretrained("/data/models/Helsinki-NLP/opus-mt-zh-en")
model = AutoModelForSeq2SeqLM.from_pretrained("/data/models/Helsinki-NLP/opus-mt-zh-en")content = ['你好 世界', '哈哈哈哈']inputs = tokenizer(content, return_tensors="pt", padding=True)
translated_tokens = model.generate(**inputs, )
for translated in tokenizer.batch_decode(translated_tokens, skip_special_tokens=True):print(translated)

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipelinetokenizer = AutoTokenizer.from_pretrained("/data/models/Helsinki-NLP/opus-mt-zh-en")
model = AutoModelForSeq2SeqLM.from_pretrained("/data/models/Helsinki-NLP/opus-mt-zh-en")translator = pipeline('translation',model=model,tokenizer=tokenizer,src_lang='zho_Hans',tgt_lang='eng_Latn',max_length=512
)
print(translator(["你好 世界", "青春", ]))