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

- Xet hash:
- 1828d3759f44fcfb995a47bd83064382affe6d1870dad2fecde2744562afdcd0
- Size of remote file:
- 665 kB
- SHA256:
- 010e040c3c5e9257a050fea942d3e06a547b6a6402ccd6c77504a6b82750cd3e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.