Instructions to use jgrc3/pfeiffer_adapter_classification_noPre with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use jgrc3/pfeiffer_adapter_classification_noPre with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("roberta-base") model.load_adapter("jgrc3/pfeiffer_adapter_classification_noPre", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model_head.bin from jgrc3/pfeiffer_adapter_classification_noPre: direct link, hf CLI and curl.
- Browser
- Download file 2.37 MB
-
https://huggingface.co/jgrc3/pfeiffer_adapter_classification_noPre/resolve/main/pytorch_model_head.bin
- Command line
-
hf download hf://jgrc3/pfeiffer_adapter_classification_noPre/pytorch_model_head.bin
-
curl -L -o pytorch_model_head.bin https://huggingface.co/jgrc3/pfeiffer_adapter_classification_noPre/resolve/main/pytorch_model_head.bin
2.37 MB
- Xet hash:
- 64c3b850550913b9ba0f760f2d78a7145dbe95d22b3b9e91e4e865f847ab50e6
- Size of remote file:
- 2.37 MB
- SHA256:
- 2f4b773f63e8b4c79e07cc76e596e607b96ffb7a576b50f410c7ead95edc6a02
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