Text Generation
fastText
Amharic
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-semitic_ethiopic
Instructions to use wikilangs/am with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/am with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/am", "model.bin")) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f060d51cad092fe7b9d73795a1e50298bae22e1ae8df8d3a27373693a65753f
- Size of remote file:
- 300 kB
- SHA256:
- ad5c361634d826f85a00a861a3aac431b960daae8e30d389a26b10f223079031
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.