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

- Xet hash:
- 37dc2d8d5800ae927faa30efea21993f562e12b2982aa0439ed3e6f3849d6b6b
- Size of remote file:
- 374 kB
- SHA256:
- 88ccaf7d4deebd3394bfa43f522d4156b65a804287178e7d353d1987a39361ba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.