| | --- |
| | license: apache-2.0 |
| | tags: |
| | - word2vec |
| | datasets: |
| | - wikipedia |
| | language: |
| | - de |
| | --- |
| | |
| | ## Information |
| | Pretrained Word2vec in German. 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_dewiki_20180420_100d", filename="dewiki_20180420_100d.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} |
| | } |
| | ``` |
| |
|
