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1from transformers import T5ForConditionalGeneration, T5Tokenizer
2
3model_name = 'utrobinmv/t5_translate_en_ru_zh_small_1024'
4model = T5ForConditionalGeneration.from_pretrained(model_name)
5tokenizer = T5Tokenizer.from_pretrained(model_name)
6
7prefix = 'translate to zh: '
8src_text = prefix + "Цель разработки — предоставить пользователям личного синхронного переводчика."
9
10# translate Russian to Chinese
11input_ids = tokenizer(src_text, return_tensors="pt")
12
13generated_tokens = model.generate(**input_ids)
14
15result = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
16print(result)
17#开发的目的是为用户提供个人同步翻译。1from transformers import T5ForConditionalGeneration, T5Tokenizer
2
3model_name = 'utrobinmv/t5_translate_en_ru_zh_small_1024'
4model = T5ForConditionalGeneration.from_pretrained(model_name)
5tokenizer = T5Tokenizer.from_pretrained(model_name)
6
7prefix = 'translate to ru: '
8src_text = prefix + "开发的目的是为用户提供个人同步翻译。"
9
10# translate Russian to Chinese
11input_ids = tokenizer(src_text, return_tensors="pt")
12
13generated_tokens = model.generate(**input_ids)
14
15result = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
16print(result)
17#Цель разработки - предоставить пользователям персональный синхронный перевод.