Text Generation
fastText
Russia Buriat
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-mongolic
Instructions to use wikilangs/bxr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/bxr with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/bxr", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/embedding_similarity.png from wikilangs/bxr: direct link, hf CLI and curl.
- Browser
- Download file 154 kB
-
https://huggingface.co/wikilangs/bxr/resolve/main/visualizations/embedding_similarity.png
- Command line
-
hf download hf://wikilangs/bxr/visualizations/embedding_similarity.png
-
curl -L -o embedding_similarity.png https://huggingface.co/wikilangs/bxr/resolve/main/visualizations/embedding_similarity.png
154 kB

- Xet hash:
- 2e9dbfdea238da073fe69725a6c65273168c6ecbae5a1fbf3036fe7929e65ab3
- Size of remote file:
- 154 kB
- SHA256:
- ca890af98049ce326bc8c07eb78480943df8b4eb9b7b3acfdde68018cee0aa5c
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