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:
- e5b6cc351d82123a84c5b304c90e150671e1a9e8dbf1f87a633c6ac78adbdc6b
- Size of remote file:
- 709 kB
- SHA256:
- 381d346c32a0a2171f561b3373852e9df38d598f3626a7704647b328b806d04c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.