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

- Xet hash:
- 661757b3d06baa8b2681e41056ad7d05a3c50343d1ea6fbf616807255d2f64ee
- Size of remote file:
- 155 kB
- SHA256:
- 4f6ea2e899b544c866c5e29d13eb8a34f500e214a9dc35725c04f0e4bdf5fe5b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.