Bert-embedding

The purpose:

To extract bert embedding from text, we just want to get the embedding by bert.

The background:

Bert as service is not suitable for my work requirement.

Where I collect these methods:

from github list and google, the most related ones.

Method collection

( including some out of date method to give a whole description )

1) Bert-embedding:

https://github.com/imgarylai/bert-embedding you can use it by:

pip install bert-embedding

[It will probably the first one appearing in the related list. However ,it is deprecated because the author has no time to maintain it, its output shows some unreasonable points.]

eg. an issue in bert-embedding

When using 
bert_embedding = BertEmbedding(model='bert_12_768_12', dataset_name='wiki_cn')
res = bert_embedding(u'火箭险胜勇士')
There comes 2 [UNK] for each Chinese character, like this:
[(['[UNK]', '火', '[UNK]'], ...)]
and it is followed by 3 768-dimension arrays.

Which one is exactly the word embedding for "火"?  
The author doesn't give answer for this.

2)

https://github.com/weiarqq/bert-embedding

• Implemented by tensorflow
• Suitable for industrial use
• Easy to use

3)

https://github.com/YC-wind

• Based on bert as service
• Implemented by tensorflow

4)

https://mccormickml.com/2019/05/14/BERT-word-embeddings-tutorial/

• This is one tutorial for getting embedding from Chris McCormick and Nick Ryan.
• Very simple and easy to scan.
• The original version is jupyternook, I do some minor changes for my chinese usage, maybe you can download bert-word-embedding.py in this repository directly.