Text Generation
fastText
Pāli
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-indoaryan_central
Instructions to use wikilangs/pi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/pi with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/pi", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 32bff9e5048824ef56de11cb66171e40375bf23313542429e4c411ca17cdd6c5
- Size of remote file:
- 244 kB
- SHA256:
- a48da66d768b2e04951dfecae2478a5df3be0e798a7a771ba59ca15d2a4fc8b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.