Text Generation
fastText
Bambara
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-atlantic_other
Instructions to use wikilangs/bm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/bm with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/bm", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/performance_dashboard.png from wikilangs/bm: direct link, hf CLI and curl.
- Browser
- Download file 365 kB
-
https://huggingface.co/wikilangs/bm/resolve/main/visualizations/performance_dashboard.png
- Command line
-
hf download hf://wikilangs/bm/visualizations/performance_dashboard.png
-
curl -L -o performance_dashboard.png https://huggingface.co/wikilangs/bm/resolve/main/visualizations/performance_dashboard.png
365 kB

- Xet hash:
- 3b30b09c352e442edd6d67a6e38250a9294b5b8bf0225b14dc5246ed24f23a33
- Size of remote file:
- 365 kB
- SHA256:
- 5213de95ac48d7bc28fb20fdac0e68302ea95f5a2dde335ff6b72de5d8ad65d3
·
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