Text Generation
fastText
Rusyn
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-slavic_east
Instructions to use wikilangs/rue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/rue with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/rue", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/embedding_tsne_multilingual.png from wikilangs/rue: direct link, hf CLI and curl.
- Browser
- Download file 234 kB
-
https://huggingface.co/wikilangs/rue/resolve/main/visualizations/embedding_tsne_multilingual.png
- Command line
-
hf download hf://wikilangs/rue/visualizations/embedding_tsne_multilingual.png
-
curl -L -o embedding_tsne_multilingual.png https://huggingface.co/wikilangs/rue/resolve/main/visualizations/embedding_tsne_multilingual.png
234 kB

- Xet hash:
- c69c93728bb75e40e7918cab7e0ef190bd3d41cfeb8971b15e4065d7b48ff1cb
- Size of remote file:
- 234 kB
- SHA256:
- 1a1db4aa08a6c2b6f66c09d0cc6d2954b98052e9ec182170fdf76ead00de7a2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.