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:
- 32d0f35f99117315659e8cb8692ac9050f5977fa428d5fbb43b5679f71b8fe14
- Size of remote file:
- 115 kB
- SHA256:
- a087ca3c3daec0e21e50089d1c0afb39b5bbe298011021208e4a543583be8f1d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.