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

- Xet hash:
- a030955d0cd1fb2d638c0699776407c15d7057d7f1a0f2e0d71814ce9475fd62
- Size of remote file:
- 231 kB
- SHA256:
- f16030792e07a09a7f108e16034991b4766139dbf9096538399d1021e09dd493
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.