Text Generation
fastText
Kölsch
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-germanic_west_continental
Instructions to use wikilangs/ksh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/ksh with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/ksh", "model.bin")) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8d03ded22fdfdc0ab266a68d7c367e58216e0983c7c24e92b292efb04ab4395
- Size of remote file:
- 259 MB
- SHA256:
- f0589aadf63e863b9efe8a78f2b47672e06caf8b147beabaa3d0cd265dce5f5b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.