<commit_before># doc2vec
C++ implement of <NAME>'s word/document/sentence embedding. You may want to feel the basic idea from Mikolov's two orignal papers, [word2vec](http://arxiv.org/pdf/1301.3781.pdf) and [doc2vec](http://cs.stanford.edu/~quocle/paragraph_vector.pdf)

# Dependencies
g++ </br>
[gtest 1.7+](http://code.google.com/p/googletest/) if you wanna run test suites </br>

# Why did I rewrite it in C++?
There are a few pretty nice projects like [google's word2vec](https://code.google.com/p/word2vec/) and [gensim](https://github.com/piskvorky/gensim) has already implemented the algorithm. I rewrite it for following reasons:</br>
1> speed. I believe c/c++ version has the best speed on CPU. In fact, according to test on same machine and runing with same number of theads, Fully optimized gensim verison got ~100K words/s, whereas c++ version achieved 200K words/s </br>
2> functionality. After I awared the advantage of c++ in term of efficiency, I found few open-source project 

# Getting started


<commit_msg>add readme<commit_after># doc2vec
C++ implement of <NAME>'s word/document/sentence embedding. You may want to feel the basic idea from Mikolov's two orignal papers, [word2vec](http://arxiv.org/pdf/1301.3781.pdf) and [doc2vec](http://cs.stanford.edu/~quocle/paragraph_vector.pdf)

# Dependencies
g++ </br>
[gtest 1.7+](http://code.google.com/p/googletest/) if you wanna run test suites </br>

# Why did I rewrite it in C++?
There are a few pretty nice projects like [google's word2vec](https://code.google.com/p/word2vec/) and [gensim](https://github.com/piskvorky/gensim) has already implemented the algorithm. I rewrite it for following reasons:</br>
1> speed. I believe c/c++ version has the best speed on CPU. In fact, according to test on same machine and runing with same number of theads, Fully optimized gensim verison got ~100K words/s, whereas c++ version achieved 200K words/s </br>
2> functionality. After I awared the advantage of c/c++ in term of efficiency, I found few open-source project 

# Getting started



{'fraction_non_alphanumeric': 0.11544081831466146, 'fraction_numerical': 0.022406234778373113, 'mean_word_length': 4.506702412868632, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 17, 'https://': 4, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '4833051', 'n_tokens_mistral': 679, 'n_tokens_neox': 627, 'n_words': 257}