Text Generation
fastText
Swedish
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-germanic_north
Instructions to use wikilangs/sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/sv with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/sv", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/embedding_tsne_multilingual.png from wikilangs/sv: direct link, hf CLI and curl.
- Browser
- Download file 226 kB
-
https://huggingface.co/wikilangs/sv/resolve/main/visualizations/embedding_tsne_multilingual.png
- Command line
-
hf download hf://wikilangs/sv/visualizations/embedding_tsne_multilingual.png
-
curl -L -o embedding_tsne_multilingual.png https://huggingface.co/wikilangs/sv/resolve/main/visualizations/embedding_tsne_multilingual.png
226 kB

- Xet hash:
- 821e709b5291174ceb4db47c09cbf6c580dd8124dbce52e99f462e116f355fd0
- Size of remote file:
- 226 kB
- SHA256:
- 81ca146f73444be6cc42d88186e98b7bba62263eff8ea8c14724e2085da8bab2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.