Text Generation
fastText
Zhuang
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-taikadai_other
Instructions to use wikilangs/za with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/za with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/za", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/tsne_words.png from wikilangs/za: direct link, hf CLI and curl.
- Browser
- Download file 734 kB
-
https://huggingface.co/wikilangs/za/resolve/main/visualizations/tsne_words.png
- Command line
-
hf download hf://wikilangs/za/visualizations/tsne_words.png
-
curl -L -o tsne_words.png https://huggingface.co/wikilangs/za/resolve/main/visualizations/tsne_words.png
734 kB

- Xet hash:
- 744a94cb1b9dd71ac2f3ccc26f2317f18ce94763631278f4e01ff11c1b468561
- Size of remote file:
- 734 kB
- SHA256:
- c0cd94d9a9720c45fee323edf441d1a06bcd9b3692698b40f9b284781d99190f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.