Text Generation
fastText
Venetian
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-romance_galloitalic
Instructions to use wikilangs/vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/vec with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/vec", "model.bin")) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dde38f09bc31cf46e3d7839bef0c3d85cff8ee8d4f0871c08e1792f404c71ca
- Size of remote file:
- 507 kB
- SHA256:
- 9c9bb143d50649591d99625d91eb1bd601ea9d89f3184b026a7d21dda801e3c3
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