Text Generation
fastText
Pa'o Karen
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-tibetoburman_other
Instructions to use wikilangs/blk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/blk with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/blk", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/zipf_law.png from wikilangs/blk: direct link, hf CLI and curl.
- Browser
- Download file 110 kB
-
https://huggingface.co/wikilangs/blk/resolve/main/visualizations/zipf_law.png
- Command line
-
hf download hf://wikilangs/blk/visualizations/zipf_law.png
-
curl -L -o zipf_law.png https://huggingface.co/wikilangs/blk/resolve/main/visualizations/zipf_law.png
110 kB

- Xet hash:
- 31ca4fd4530737cb07d39cbef00a115878954a85bafb944f7df5cdf17c58e465
- Size of remote file:
- 110 kB
- SHA256:
- fe95b53022e47afa1b47fe49c537c8dfaafdfb1800f09fc53925768ab2a348d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.