Text Generation
fastText
Ladino
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-semitic_hebrew
Instructions to use wikilangs/lad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/lad with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/lad", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/tsne_sentences.png from wikilangs/lad: direct link, hf CLI and curl.
- Browser
- Download file 265 kB
-
https://huggingface.co/wikilangs/lad/resolve/main/visualizations/tsne_sentences.png
- Command line
-
hf download hf://wikilangs/lad/visualizations/tsne_sentences.png
-
curl -L -o tsne_sentences.png https://huggingface.co/wikilangs/lad/resolve/main/visualizations/tsne_sentences.png
265 kB

- Xet hash:
- 5a6ab89ba13d674a70121172eea8c18fc2cc8f86af4b34566f0cb00a4ae8a1cc
- Size of remote file:
- 265 kB
- SHA256:
- 1ce82fccfcc9b87821de6135d90009f9cf0ccd109ca3beb4459fe872f70a7e0d
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