Text Generation
fastText
Neapolitan
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_galloitalic
Instructions to use wikilangs/nap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/nap with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/nap", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- c232937f4cde94c9d7dfe984943b307800db3afa9908d411c691372ddc09769e
- Size of remote file:
- 243 kB
- SHA256:
- 107ab96349dcdc9f475412e983f3ba43d9184c99069f461e4b71a0bab3a5d341
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.