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

- Xet hash:
- b32719bf8d8894412c77f0ae4a423706a0472d7bdd513ac64989e672023ac76a
- Size of remote file:
- 283 kB
- SHA256:
- 1b489aa35360c195e0d4ac377f772d42526dd3b8df09ac1eee8a95e07e81c33d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.