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:
- 33285fbd828f63bc0635d36e80c50026c5b64bf0eb0c5a4ca88d174c09b8dce9
- Size of remote file:
- 272 kB
- SHA256:
- e16db6d7fa2f78c4b0bfe26dfa4119daf8c9cd1c8e0c9e2d462777440bdd6797
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.