Text Generation
fastText
Burmese
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-tibetoburman_burmese
Instructions to use wikilangs/my with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/my with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/my", "model.bin")) - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 41829aea1fe39feeeac04836209967dc1a44365f8441ba05b1704420aff31770
- Size of remote file:
- 613 kB
- SHA256:
- 3a002e6434b3742e24ad1e0b62af5f425dd9dd2d80f6b46edc9e82fc3c16b524
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.