Text Generation
fastText
N'Ko
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-constructed_other
Instructions to use wikilangs/nqo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/nqo with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/nqo", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/embedding_tsne_multilingual.png from wikilangs/nqo: direct link, hf CLI and curl.
- Browser
- Download file 267 kB
-
https://huggingface.co/wikilangs/nqo/resolve/main/visualizations/embedding_tsne_multilingual.png
- Command line
-
hf download hf://wikilangs/nqo/visualizations/embedding_tsne_multilingual.png
-
curl -L -o embedding_tsne_multilingual.png https://huggingface.co/wikilangs/nqo/resolve/main/visualizations/embedding_tsne_multilingual.png
267 kB

- Xet hash:
- 562b4a5a6ec3323e304da15f2d17901373085134e02cb75395231ece3e80b1ca
- Size of remote file:
- 267 kB
- SHA256:
- 459efdd3a8640478cd00a70beb8db36d673f00cf80f8339da5be49c95ccb372a
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