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

- Xet hash:
- fc8f13831ef1277e2c9a850a423af6244d4bf7324e2d3d03968d54f8c6da2e0e
- Size of remote file:
- 273 kB
- SHA256:
- 1fe0574479123ca297ad757cacb659fec90fb7fa4c6ddc9da24c91038cb0bb38
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.