Instructions to use eja67/MBIAS_adapter_fsame with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eja67/MBIAS_adapter_fsame with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eja67/MBIAS_adapter_fsame", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- abbb35ac9c3e961c0d9e4b3d0b506b16e6049798ec6caddd481ab474d8dc8cda
- Size of remote file:
- 5.78 kB
- SHA256:
- dcbb852d488af82cfdd07ca31228f03469e82f0832e523bc99e72854f02f2109
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