Text Generation
fastText
Ndonga
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_central
Instructions to use wikilangs/ng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/ng with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/ng", "model.bin")) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4261fcb14523deb7210115ea04c2773a62b2142bf16919e16dce8f2c9a619e6
- Size of remote file:
- 256 MB
- SHA256:
- fa58d081dda754238780d73dc92ccd9120de5c25f3e7700818762f81f1912421
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.