Text Generation
fastText
Asturian
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/ast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/ast with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/ast", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/tsne_words.png from wikilangs/ast: direct link, hf CLI and curl.
- Browser
- Download file 667 kB
-
https://huggingface.co/wikilangs/ast/resolve/main/visualizations/tsne_words.png
- Command line
-
hf download hf://wikilangs/ast/visualizations/tsne_words.png
-
curl -L -o tsne_words.png https://huggingface.co/wikilangs/ast/resolve/main/visualizations/tsne_words.png
667 kB

- Xet hash:
- 4d2994728bb76accdadde1efa93e26bc406d8a807e777ef2cdbb119e266a5f59
- Size of remote file:
- 667 kB
- SHA256:
- f9f72a0209727f896ecab6f290d1948445297819e8c2eaa18690e1d59f264a39
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.