vocab.txt & vectors.txt structure

[RaBa01]

hi
i build my model with gensim Word2Vec and i want to learn my model with NER.
is there any document to explain vocab.txt and vectors.txt structure?

i used this script:
bin/dl-ner.py ner.dnn -t train+dev
—vocab vocab.txt —vectors vectors.txt
—caps —suffix —suffixes —gazetteer eng.list
-e 40 -l 0.01 -w 5 -n 300 -v

[kjyong]

I tried to analyze the code and converted gensim word2vec model to input for deepnl.
The format I tried is like below, and it works.
[vocab.txt]

word1
word2
word3
...

[vectors.txt]

2 3
word1 1.0 2.0 3.0
word2 2.3 3.5 1.2
...

the first line in vectors.txt means number of words and their dimension.