Text Generation
fastText
Udmurt
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_permian
Instructions to use wikilangs/udm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/udm with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/udm", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/tsne_sentences.png from wikilangs/udm: direct link, hf CLI and curl.
- Browser
- Download file 272 kB
-
https://huggingface.co/wikilangs/udm/resolve/main/visualizations/tsne_sentences.png
- Command line
-
hf download hf://wikilangs/udm/visualizations/tsne_sentences.png
-
curl -L -o tsne_sentences.png https://huggingface.co/wikilangs/udm/resolve/main/visualizations/tsne_sentences.png
272 kB

- Xet hash:
- e4b138fbb2eb2062f3c446ac309ce5602a046e42dea65e174b4415d7ca94a611
- Size of remote file:
- 272 kB
- SHA256:
- 60c000a193f1480ad585ede2c8ab49ab2738b80d43489dcb77605d9d541d1e03
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.