Text Generation
fastText
Northern Sami
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_saami
Instructions to use wikilangs/se with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/se with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/se", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 8c3ab651e7a218e13c264cf5de97e35d32e7194bf43cfb260d273db726e3d881
- Size of remote file:
- 224 kB
- SHA256:
- b61e91352de8ac42b7a457968b082d6ea4d9969f0a44e6168944341ff9071c54
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.