Text Generation
fastText
Saterfriesisch
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/stq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/stq with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/stq", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- a51ccdfc85cb582a8df44be0ac7fb9bd76c4cb66a5d221decb2336d6ac033592
- Size of remote file:
- 366 kB
- SHA256:
- 7fbde4d0c7a6460c66e795948275f0e332dd0d55a26918b4611dae2a7d9687f0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.