Instructions to use SI2M-Lab/DarijaBERT-mix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SI2M-Lab/DarijaBERT-mix with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SI2M-Lab/DarijaBERT-mix", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SI2M-Lab/DarijaBERT-mix: direct link, hf CLI and curl.
- Browser
- Download file 836 MB
-
https://huggingface.co/SI2M-Lab/DarijaBERT-mix/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SI2M-Lab/DarijaBERT-mix/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SI2M-Lab/DarijaBERT-mix/resolve/main/pytorch_model.bin
836 MB
- Xet hash:
- 3d8b08ed86ca520f5d2b839d246e5096e4f568ae7326fe1dfa5a2e948d8cc03a
- Size of remote file:
- 836 MB
- SHA256:
- 0a738e7884564f5e4bccfd4358ced7b5564cc94a039d11e408d41b9a41fa94c5
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