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

- Xet hash:
- f07ebb6c446ea8bff351674b98b189d08b8482cd1c8fcbf729a635c24433f435
- Size of remote file:
- 413 kB
- SHA256:
- 6ecb703cc70c479bfcc5b836abe5bd886c5d7651b235bfafe90172f2d67ca68c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.