Text Generation
fastText
Tumbuka
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-bantu_eastern
Instructions to use wikilangs/tum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/tum with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/tum", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/zipf_law.png from wikilangs/tum: direct link, hf CLI and curl.
- Browser
- Download file 105 kB
-
https://huggingface.co/wikilangs/tum/resolve/main/visualizations/zipf_law.png
- Command line
-
hf download hf://wikilangs/tum/visualizations/zipf_law.png
-
curl -L -o zipf_law.png https://huggingface.co/wikilangs/tum/resolve/main/visualizations/zipf_law.png
105 kB

- Xet hash:
- 276a5bc6e45ab83b3086139bdd095a806af9426479e1f5d38cca4129f4f0bd06
- Size of remote file:
- 105 kB
- SHA256:
- 0d7a6fdc23f2562d424c7ef5cfe227fc5b65f6405eff24e7c5996f124c751df8
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