Text Generation
fastText
Betawi
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-austronesian_malay
Instructions to use wikilangs/bew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/bew with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/bew", "model.bin")) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4c83d6434f33313ad2d1ac0d809adbeb036e3b8737341c2fcce86281e35aca4
- Size of remote file:
- 258 MB
- SHA256:
- f67005fdd1a646c4cab4fa8d00ad418d61e5a5997909d2692a20c93d633cb841
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.