semvec/pypi-packages huggingface dataset:
bert-sent-encoding 0.2.0
A bert sentence encoding tool
License: BSD

This is a bert sentence encoding tool.

## Install

    pip install --index-url https://pypi.python.org/simple/ bert-sent-encoding==0.2.0
or

    git clone ssh://git@gitlab.leihuo.netease.com:32200/shaojianzhi/bert-sent-encoding.git
    cd bert-sent-encoding
    python setup.py install
## Use

    from bert_sent_encoding import bert_sent_encoding # 1st line
    bse = bert_sent_encoding(model_path='bert_sent_encoding/model/chinese_L-12_H-768_A-12', seq_length=64, batch_size=8) # 2nd line
    vector = bse.get_vector('你吃饭了吗', word_vector=False, layer=-1)   # 3rd line 1. get vector of string
    vectors = bse.get_vector(['你吃饭了吗', '已经吃了呀'], word_vector=False, layer=-1)  # 4th line 2. get vector list of strings
    bse.write_txt2vector(input_file, output_file, word_vector=False, layer=-1)   # 5th line 3. get and write vectors of strings


### for 2nd line:
    bse = bert_sent_encoding(model_path='bert_sent_encoding/model/chinese_L-12_H-768_A-12', seq_length=64, batch_size=8)
    *model_path is required, seq_length and batch_size are optional
### for 3rd, 4th and 5th lines
    vector = bse.get_vector('你吃饭了吗', word_vector=False, layer=-1)   # 3rd line 1. get vector of string
    vectors = bse.get_vector(['你吃饭了吗', '已经吃了呀'], word_vector=False, layer=-1)  # 4th line 2. get vector list of strings
    bse.write_txt2vector(input_file, output_file, word_vector=False, layer=-1)   # 5th line 3. get and write vectors of strings
    *word_vector and layer are optional*

### for 5th line:
    bse.write_txt2vector(input_file, output_file)   # 3. get and write vectors of strings
path of **input_file** and **output_file** are defined by user and below is content of **input_file**:

    the first line text
    the second line text
    ...