Text Generation
fastText
Inari Sami
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-uralic_saami
Instructions to use wikilangs/smn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/smn with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/smn", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/zipf_law.png from wikilangs/smn: direct link, hf CLI and curl.
- Browser
- Download file 107 kB
-
https://huggingface.co/wikilangs/smn/resolve/main/visualizations/zipf_law.png
- Command line
-
hf download hf://wikilangs/smn/visualizations/zipf_law.png
-
curl -L -o zipf_law.png https://huggingface.co/wikilangs/smn/resolve/main/visualizations/zipf_law.png
107 kB

- Xet hash:
- dfd9b7974e5a3c46bde367e600408b60903bc7ac7e609be35a35d95e956c7bab
- Size of remote file:
- 107 kB
- SHA256:
- 51321c77468a91a27567594d8e6da3ea4be74b3693b57d471a952eee1195cf6b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.