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

- Xet hash:
- 7ac68d3af894107dd80f665ea6ac55c9c0d33d0992dad344a3dc10ad2afe16cc
- Size of remote file:
- 150 kB
- SHA256:
- 2e2745e60dd4228102454f65f2e7068a6524f57840d3b546272c5e4c53ede554
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.