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
Download visualizations/performance_dashboard.png from wikilangs/vec: direct link, hf CLI and curl.
- Browser
- Download file 391 kB
-
https://huggingface.co/wikilangs/vec/resolve/main/visualizations/performance_dashboard.png
- Command line
-
hf download hf://wikilangs/vec/visualizations/performance_dashboard.png
-
curl -L -o performance_dashboard.png https://huggingface.co/wikilangs/vec/resolve/main/visualizations/performance_dashboard.png
391 kB

- Xet hash:
- faa6dcc5a718b5f1f6b7cacaa3fc4e3868c50762020547d55c0765f3af2bbddf
- Size of remote file:
- 391 kB
- SHA256:
- c5249998c14bdf999ec0d90694ef3a724e8d316511d88fc141a72504694036b7
·
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