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:
- 084a3c5195b9eb176c87aa6926cced05ecb30427c07e085372ff6d00b61c01e5
- Size of remote file:
- 159 kB
- SHA256:
- 90bc041be37fe7899985f79dac4bd05958bb07a2c66928dcb3297d0cc6fe77c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.