Write model description

README.md

@@ -1,3 +1,85 @@
 ---
 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."
+    "ギルガメッシュ討伐戦",  # "the battle for gilgamesh's domain"
+    "ギルガメッシュ討伐戦に行ってきます。一緒に行きましょうか？",  # "I'm going to the battle for gilgamesh's domain. shall we go together?"
+    "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,
+}
+```
+
+
+