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

- Xet hash:
- 84a5a9ade735b1c8be76b9ee32ff4bfddd4d521f5dc9055f4afe02810a52362d
- Size of remote file:
- 105 kB
- SHA256:
- 68eb79f9f064e3670066113200f4d41b7a767005ce09e175ebe2b82a9eefa542
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.