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
- Xet hash:
- 0c35847689dac87e568c2171aa87a3926abbea48b3056016055c662709f1f4cb
- Size of remote file:
- 504 kB
- SHA256:
- 242306074b42b2731865a15cce9984d5736ffc4699031020f06258b35683a505
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.