Instructions to use laurievb/OpenLID-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use laurievb/OpenLID-v2 with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("laurievb/OpenLID-v2", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download model.bin from laurievb/OpenLID-v2: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/laurievb/OpenLID-v2/resolve/main/model.bin
- Command line
-
hf download hf://laurievb/OpenLID-v2/model.bin
-
curl -L -o model.bin https://huggingface.co/laurievb/OpenLID-v2/resolve/main/model.bin
1.22 GB
- Xet hash:
- c7d24c514aa9366ce774f01cee8a19c2bbdd9d9dc52c87d13de5f2ecd7e1c1e7
- Size of remote file:
- 1.22 GB
- SHA256:
- f01b47c6182909291a3394f77f682031aaeade346e443c4e496e94bd2a9fa703
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.