Update README.md

README.md

@@ -1,3 +1,60 @@
 ---
 license: cc-by-nc-sa-4.0
+datasets:
+- wikipedia
+- cc100
+language:
+- ja
+library_name: transformers
+pipeline_tag: fill-mask
 ---
+
+BERT-base (Nothing + Unigram)
+===
+
+## How to load the tokenizer
+Please download the dictionary file for Nothing + Unigram from [our GitHub repository](https://github.com/hitachi-nlp/compare-ja-tokenizer/blob/public/data/dict/nothing_unigram.json).
+Then you can load the tokenizer by specifying the path of the dictionary file to `dict_path`.
+
+```python
+from typing import Optional
+
+from tokenizers import Tokenizer, NormalizedString, PreTokenizedString
+from tokenizers.processors import BertProcessing
+from tokenizers.pre_tokenizers import PreTokenizer
+from transformers import PreTrainedTokenizerFast
+
+# load a tokenizer
+dict_path = /path/to/nothing_unigram.json
+tokenizer = Tokenizer.from_file(dict_path)
+tokenizer.post_processor = BertProcessing(
+    cls=("[CLS]", tokenizer.token_to_id('[CLS]')),
+    sep=("[SEP]", tokenizer.token_to_id('[SEP]'))
+)
+
+# convert to PreTrainedTokenizerFast
+tokenizer = PreTrainedTokenizerFast(
+    tokenizer_object=tokenizer,
+    unk_token='[UNK]',
+    cls_token='[CLS]',
+    sep_token='[SEP]',
+    pad_token='[PAD]',
+    mask_token='[MASK]'
+)
+```
+
+```python
+# Test
+test_str = "こんにちは。私は形態素解析器について研究をしています。"
+tokenizer.convert_ids_to_tokens(tokenizer(test_str).input_ids)
+# -> ['[CLS]','こん','に','ち','は','。','私','は','形態','素','解析','器','について','研究','をして','います','。','[SEP]']
+```
+
+## How to load the model
+```python
+from transformers import AutoModelForMaskedLM
+model = AutoModelForMaskedLM.from_pretrained("hitachi-nlp/bert-base_nothing-unigram")
+```
+
+
+**See [our repository](https://github.com/hitachi-nlp/compare-ja-tokenizer) for more details!**