Skip to main content

Methods for evaluating low-resource word embedding models trained with gensim

Project description

gensim-evaluations

This library provides methods for evaluating word embedding models loaded with gensim. Currently, it implements two methods designed specifically for the evaluation of low-resource models. The code allows users to automatically create custom test sets in any of the 581 languages supported by Wikidata and then to evaluate on them using the OddOneOut and Topk methods introduced in this paper.

For more details visit the github repository

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gensim_evaluations-0.1.2.tar.gz (7.4 kB view hashes)

Uploaded Source

Built Distribution

gensim_evaluations-0.1.2-py3-none-any.whl (15.7 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page