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

- Xet hash:
- 067153f54a76896f4710f70e98772246ee75b2dcb344090be3de90eb4466cd37
- Size of remote file:
- 675 kB
- SHA256:
- aa88154cbdcb9b7a2193482eae83b202c59c4a7afa82c4d48c7a8c5c180a0faa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.