Text Generation
fastText
Macedonian
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-slavic_south
Instructions to use wikilangs/mk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/mk with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/mk", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 0009ec4dce0863e9794e7fa652611980ce6da2c4ef0320327df6eb3a9f73a41f
- Size of remote file:
- 365 kB
- SHA256:
- f74832f1689be3c2634ccdb2ba45b5a0bfa7156824e5387548c8e0c9d8f17605
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.