Instructions to use jgrc3/seqBN_adapter_classification_noPre with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use jgrc3/seqBN_adapter_classification_noPre with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("roberta-base") model.load_adapter("jgrc3/seqBN_adapter_classification_noPre", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model_head.bin from jgrc3/seqBN_adapter_classification_noPre: direct link, hf CLI and curl.
- Browser
- Download file 2.37 MB
-
https://huggingface.co/jgrc3/seqBN_adapter_classification_noPre/resolve/main/pytorch_model_head.bin
- Command line
-
hf download hf://jgrc3/seqBN_adapter_classification_noPre/pytorch_model_head.bin
-
curl -L -o pytorch_model_head.bin https://huggingface.co/jgrc3/seqBN_adapter_classification_noPre/resolve/main/pytorch_model_head.bin
2.37 MB
- Xet hash:
- 59b296d574dc25c010ab039234a00434f59656e8436be373f5d78f7875319b93
- Size of remote file:
- 2.37 MB
- SHA256:
- 798a594306b770643f22e8f8e563a025bf6bcbc28de3fe2b47440909d3bae083
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