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

- Xet hash:
- b4cd1ae7c105831ac1dcbdf49317c0a1778acfa1bacb5423ddc393a446fee4ad
- Size of remote file:
- 105 kB
- SHA256:
- 4e263e2bb882811a941a0b34ce0ebeaee3c7a8f2cad3f1304bb1425109ccce49
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.