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

- Xet hash:
- 7327f470965e1022760e3a8e9a1bcb0ace0c6a34ab0a7b864e140bffe0a431f5
- Size of remote file:
- 345 kB
- SHA256:
- 52ba7fa2e9216eee197b26ae023a406372ef783fa64e60d3a30c207ce5d3a399
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.