Metadata-Version: 2.1
Name: vec2graph
Version: 0.2.4
Summary: Mini-library for producing graph visualizations from embedding models
Home-page: https://github.com/lizaku/vec2graph
Author: Nadezda Katricheva, Alyaxey Yaskevich, Anastasiya Lisitsina, Tamara Zhordaniya, Andrey Kutuzov, Elizaveta Kuzmenko
Author-email: andreku@ifi.uio.no
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Utilities
Requires-Python: >=3
Description-Content-Type: text/markdown
Requires-Dist: gensim (>3.5)
Requires-Dist: smart-open (>1.8)
Requires-Dist: requests

# 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')`

