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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
...

Release files for bert-sent-encoding 0.2.0

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Source distribution (sdist)

Source distribution for bert-sent-encoding 0.2.0
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Table of built distributions (wheels) for bert-sent-encoding 0.2.0
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bert_sent_encoding-0.2.0-py3-none-any.whl Python 3 none any Details

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Release files / bert_sent_encoding-0.2.0.tar.gz

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0.2.0 This release

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