Text Generation
fastText
Pedi
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_southern
Instructions to use wikilangs/nso with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/nso with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/nso", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 1e3348ea4a2ad46e6180f0da434a2a30dc456a7aed961831178a958a008ec097
- Size of remote file:
- 154 kB
- SHA256:
- 17a8ee98c60e65c0bb01d5293e708733f8282105bd99adc26ff3121e78f373a5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.