Text Generation
fastText
Atayal
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-austronesian_formosan
Instructions to use wikilangs/tay with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/tay with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/tay", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/tsne_sentences.png from wikilangs/tay: direct link, hf CLI and curl.
- Browser
- Download file 232 kB
-
https://huggingface.co/wikilangs/tay/resolve/main/visualizations/tsne_sentences.png
- Command line
-
hf download hf://wikilangs/tay/visualizations/tsne_sentences.png
-
curl -L -o tsne_sentences.png https://huggingface.co/wikilangs/tay/resolve/main/visualizations/tsne_sentences.png
232 kB

- Xet hash:
- a5eec02ffa59761aef6e35ad5d26fc0dc52cab56538dee32c6121f46ea32d5d2
- Size of remote file:
- 232 kB
- SHA256:
- 95c0579a888842024ad5cd11327c6076bd6174117dab9041befb5610e1011dac
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.