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

- Xet hash:
- c66d41953a33391ef2e284665cddf71f957bda96c855d480b27912bd8efe1b70
- Size of remote file:
- 119 kB
- SHA256:
- 20830936e13264e922a0601df2cda33749177091f39cb1a333df7eb2d0b282b1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.