Instructions to use laurievb/OpenLID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use laurievb/OpenLID with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("laurievb/OpenLID", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download model.bin from laurievb/OpenLID: direct link, hf CLI and curl.
- Browser
- Download file 1.23 GB
-
https://huggingface.co/laurievb/OpenLID/resolve/main/model.bin
- Command line
-
hf download hf://laurievb/OpenLID/model.bin
-
curl -L -o model.bin https://huggingface.co/laurievb/OpenLID/resolve/main/model.bin
1.23 GB
- Xet hash:
- 34dffd9f76c1cc3b6aabb1ffc4028481b79fe63215992d3e50cfa023dc3f09af
- Size of remote file:
- 1.23 GB
- SHA256:
- 0e2bc6d0d3048b38c4e2e8aa77b4618108670eb91cb72544d3340f605964a78b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.