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

- Xet hash:
- e602703913e4bb72f39d234fd009da02ebddec65b0f84463335331478ee4ca73
- Size of remote file:
- 350 kB
- SHA256:
- ea5ba00da1cb294d496043645ffe8d676977528a229c87724a5ec5a88aaf0b49
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.