--- license: mit language: - ja - en pipeline_tag: translation --- # Japanese to Korean translator Japanese to Korean translator model based on [EncoderDecoderModel](https://huggingface.co/docs/transformers/model_doc/encoder-decoder)([bert-japanese](https://huggingface.co/cl-tohoku/bert-base-japanese)+[GPT2](https://huggingface.co/openai-community/gpt2)) # Usage ## Demo Please visit https://huggingface.co/spaces/sappho192/jesc-ja-en-translator-demo ## Dependencies (PyPI) - torch - transformers - fugashi - unidic-lite ## Inference ```Python import transformers import torch encoder_model_name = "cl-tohoku/bert-base-japanese-v2" decoder_model_name = "openai-community/gpt2" src_tokenizer = transformers.BertJapaneseTokenizer.from_pretrained(encoder_model_name) trg_tokenizer = transformers.PreTrainedTokenizerFast.from_pretrained(decoder_model_name) model = transformers.EncoderDecoderModel.from_pretrained("sappho192/jesc-ja-en-translator") def translate(text_src): embeddings = src_tokenizer(text_src, return_attention_mask=False, return_token_type_ids=False, return_tensors='pt') embeddings = {k: v for k, v in embeddings.items()} output = model.generate(**embeddings, max_length=512)[0, 1:-1] text_trg = trg_tokenizer.decode(output.cpu()) return text_trg texts = [ "逃げろ!", # Should be "run!" "初めまして.", # "nice to meet you." "よろしくお願いします.", # "thank you." "夜になりました", # "and then it got dark." "ご飯を食べましょう." # "let's eat." ] for text in texts: print(translate(text)) print() ``` # Dataset The dataset used to train the model is JESC(Japanese-English Subtitle Corpus). Its license is [CC-BY-SA-4.0](https://creativecommons.org/licenses/by-sa/4.0/). All data information can be accessed through following links: - Dataset link: https://nlp.stanford.edu/projects/jesc/ - Paper link: https://arxiv.org/abs/1710.10639 - Github link: https://github.com/rpryzant/JESC - Bibtex: ```bibtex @ARTICLE{pryzant_jesc_2017, author = {{Pryzant}, R. and {Chung}, Y. and {Jurafsky}, D. and {Britz}, D.}, title = "{JESC: Japanese-English Subtitle Corpus}", journal = {ArXiv e-prints}, archivePrefix = "arXiv", eprint = {1710.10639}, keywords = {Computer Science - Computation and Language}, year = 2017, month = oct, } ```