Mini-library for producing graph visualizations from embedding models
Project description
vec2graph
Mini-library for producing graph visualizations from embedding models
Code is available at https://github.com/lizaku/vec2graph
Usage
pip install vec2graph
from vec2graph import visualize
visualize(OUTPUT_DIR, MODEL, WORD)
OUTPUT_DIR is the directory to store your visualizations, MODEL is a word embedding model loaded with Gensim, WORD is your query word
For example:
model = gensim.models.KeyedVectors.load_word2vec_format('googlenews300.bin', binary=True)
visualize('tmp/graphs', model, 'apple')
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