Information
Pretrained Word2vec in English. For more information, see https://wikipedia2vec.github.io/wikipedia2vec/pretrained/.
How to use?
from gensim.models import KeyedVectors
from huggingface_hub import hf_hub_download
model = KeyedVectors.load_word2vec_format(hf_hub_download(repo_id="Word2vec/wikipedia2vec_enwiki_20180420_300d", filename="enwiki_20180420_300d.txt"))
model.most_similar("your_word")
Citation
@inproceedings{yamada2020wikipedia2vec,
title = "{W}ikipedia2{V}ec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from {W}ikipedia",
author={Yamada, Ikuya and Asai, Akari and Sakuma, Jin and Shindo, Hiroyuki and Takeda, Hideaki and Takefuji, Yoshiyasu and Matsumoto, Yuji},
booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
year = {2020},
publisher = {Association for Computational Linguistics},
pages = {23--30}
}