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

- Xet hash:
- 33bebbada7e7511136087850e8f35320c5746a6041f5a19168523f5d108eec4a
- Size of remote file:
- 280 kB
- SHA256:
- 6ce4662430c35e4e4693be3b1abd01e0f84c45ace1447c287a72470d42c762ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.