Text Generation
fastText
Abkhaz
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-caucasian_northwest
Instructions to use wikilangs/ab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/ab with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/ab", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/embedding_tsne_multilingual.png from wikilangs/ab: direct link, hf CLI and curl.
- Browser
- Download file 249 kB
-
https://huggingface.co/wikilangs/ab/resolve/main/visualizations/embedding_tsne_multilingual.png
- Command line
-
hf download hf://wikilangs/ab/visualizations/embedding_tsne_multilingual.png
-
curl -L -o embedding_tsne_multilingual.png https://huggingface.co/wikilangs/ab/resolve/main/visualizations/embedding_tsne_multilingual.png
249 kB

- Xet hash:
- 78672f350316380b8e73b20ec57487e9023a710368fd7ab69b3089abfab2c308
- Size of remote file:
- 249 kB
- SHA256:
- 271547ad930e9cc37398fc7d2e01a80b02fcbd9e036d367f8bdae00e54105bb2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.