How to Train GloVe algorithm on my own corpus

Question

I tried to follow this.
But some how I wasted a lot of time ending up with nothing useful.
I just want to train a GloVe model on my own corpus (~900Mb corpu

Answer 1

your corpus should go to variable CORPUS. The vectors.txt is the output, which suppose to be useful. You can train Glove in python, but it takes more time and you need to have C compiling environment. I tried it before and won't recommend it.

Answer 2

This is how you run the model

$ git clone http://github.com/stanfordnlp/glove
$ cd glove && make

To train it on your own corpus, you just have to make changes to one file, that is demo.sh.

Remove the script from if to fi after 'make'. Replace the CORPUS name with your file name 'corpus.txt' There is another if loop at the end of file 'demo.sh'

if [ "$CORPUS" = 'text8' ]; then

Replace text8 with your file name.

Run the demo.sh once the changes are made.

$ ./demo.sh

Make sure your corpus file is in the correct format.You'll need to prepare your corpus as a single text file with all words separated by one or more spaces or tabs. If your corpus has multiple documents, the documents (only) should be separated by new line characters.

Answer 3

Here is my take on this::

1. After cloning the repository, edit the demo.sh file as you have to train it using your own corpus replace the CORPUS name with your file's name.
2. Then remove the script between MAKE and CORPUS as that is for downloading an example corpus for you.
3. Then run make which will form the four files in the build folder.
4. Now run ./demo.sh which will train and do all the stuff mentioned in the script on your own corpus and output will be generated as vectors.txt file.

Note : Don't forget to keep your corpus file directly inside the Glove folder.

Answer 4

You can do it using GloVe library:

Install it: pip install glove_python

Then:

from glove import Corpus, Glove

#Creating a corpus object
corpus = Corpus() 

#Training the corpus to generate the co occurence matrix which is used in GloVe
corpus.fit(lines, window=10)

glove = Glove(no_components=5, learning_rate=0.05) 
glove.fit(corpus.matrix, epochs=30, no_threads=4, verbose=True)
glove.add_dictionary(corpus.dictionary)
glove.save('glove.model')

Reference: word vectorization using glove