Text Generation
fastText
Betawi
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-austronesian_malay
Instructions to use wikilangs/bew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/bew with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/bew", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download models/tokenizer/bew_tokenizer_64k.model from wikilangs/bew: direct link, hf CLI and curl.
- Browser
- Download file 1.38 MB
-
https://huggingface.co/wikilangs/bew/resolve/main/models/tokenizer/bew_tokenizer_64k.model
- Command line
-
hf download hf://wikilangs/bew/models/tokenizer/bew_tokenizer_64k.model
-
curl -L -o bew_tokenizer_64k.model https://huggingface.co/wikilangs/bew/resolve/main/models/tokenizer/bew_tokenizer_64k.model
1.38 MB
- Xet hash:
- 5c9df1844185bbb976426bcba3b51887e338d8f4da75232fb1baed9853fc6910
- Size of remote file:
- 1.38 MB
- SHA256:
- 99529365e2fc0dea414cae1cb7b20c351b8b62bccfe760eb5cda6c45d59e7f9b
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