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

- Xet hash:
- 129fabdfa6c2b4463de07ff69d859bc1489e85ab8f4904b82a6397546d661f5d
- Size of remote file:
- 281 kB
- SHA256:
- 8d3d67ff6bdd90be43051fb75ce40041d7dcb3b91ec6008920bbef19eccfb905
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.