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:
- a09742613f4ffc5f42d2703a80e2d655d441a68a9ff91595e2d8fe5c5b9462b1
- Size of remote file:
- 105 kB
- SHA256:
- 01f8dc3d0e4a52210473b38bb7c4225f70c83333cf2ad6f994a6882828a6a0a5
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