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

- Xet hash:
- a33787c3754af647cee92031b1bf8befcd2ee7aa20c4287d1b18d827c3e5cac4
- Size of remote file:
- 258 kB
- SHA256:
- f39fdbb2bead85d09ee961644c1b34ab8c26dc27857101e3ef46d468d5e586ca
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