Text Generation
fastText
Belarusian
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/be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/be with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/be", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/position_encoding_comparison.png from wikilangs/be: direct link, hf CLI and curl.
- Browser
- Download file 102 kB
-
https://huggingface.co/wikilangs/be/resolve/main/visualizations/position_encoding_comparison.png
- Command line
-
hf download hf://wikilangs/be/visualizations/position_encoding_comparison.png
-
curl -L -o position_encoding_comparison.png https://huggingface.co/wikilangs/be/resolve/main/visualizations/position_encoding_comparison.png
102 kB

- Xet hash:
- 76dbf70a829faaf08747318823d8e34d6014a1f1e4228447297ac88353fa05a7
- Size of remote file:
- 102 kB
- SHA256:
- b2928f979f0cefdcf07e58ed6f870e442156622b884ac2e22bc1194bade97f36
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