Text Generation
fastText
Twi
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_kwa
Instructions to use wikilangs/tw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/tw with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/tw", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 498541dc3368591826f0f57956ee1e4e518ba8cff7173dfc5f7262c7ad8f397e
- Size of remote file:
- 257 kB
- SHA256:
- ff73ac84245f16f74fea1164b8df12a6f47bc4ed4f90ec7ee772b97ffa4042d3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.