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

- Xet hash:
- 0bd86531d49ad679255c57e23cbc6ff4a4502813e6e8e073e8515df08a714447
- Size of remote file:
- 684 kB
- SHA256:
- d70310cca42044f04d42fe7f5ed89627668a5f1e12a89f2a18be7bc99e289e18
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.