Text Generation
fastText
Komi-Permyak
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-uralic_permian
Instructions to use wikilangs/koi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/koi with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/koi", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 7ccfca33e6945f2aa3bad882beae9b2c97242535c616c43ef2c5d5e91320a1e9
- Size of remote file:
- 150 kB
- SHA256:
- 1eb13c55231d53660927eeb3418b2eb58e19c1e8423dac770bc2dbbff99bd5ab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.