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

- Xet hash:
- 2dbbc3645c9af420463820e0205d8e5f819be442ab1a4caa81f0b4bdaf83e5f0
- Size of remote file:
- 107 kB
- SHA256:
- 8590fe0ca2df5de01e988583e775e1d21cf10d15d949217c5f95b4fd2960ebfa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.