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

- Xet hash:
- 4c68467ae2261cf1b4438b6e552b6962c7101f3a0f0b93cd3b3ea755d3790cca
- Size of remote file:
- 231 kB
- SHA256:
- 669244f4dc7736e742db0ec5d2b47947539fc821435781bb18f5d7e5fda922da
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.