
## Information
Pretrained Word2vec in Chinese. For more information, see [https://wikipedia2vec.github.io/wikipedia2vec/pretrained/](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_zhwiki_20180420_300d", filename="zhwiki_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}
}
```

{"language": ["zh"], "license": "apache-2.0", "tags": ["word2vec"], "datasets": ["wikipedia"]}
word2vec zh dataset:wikipedia license:apache-2.0 region:us
TAGS
#word2vec #zh #dataset-wikipedia #license-apache-2.0 #region-us 


## Information
Pretrained Word2vec in Chinese. For more information, see URL

## How to use?



## Information
Pretrained Word2vec in Chinese. For more information, see URL ## How to use?
TAGS
#word2vec #zh #dataset-wikipedia #license-apache-2.0 #region-us 
 ## Information
Pretrained Word2vec in Chinese. For more information, see URL ## How to use?