Instructions to use Nadav/PretrainedPHD-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nadav/PretrainedPHD-v5 with Transformers:
# Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("Nadav/PretrainedPHD-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 348751e7ecb0e4ed9e4875b3cd7042308e7a9fcc7b504b8e44a03b3a5780799a
- Size of remote file:
- 449 MB
- SHA256:
- 5fc35de7c7ab795f6ce22b4d822a3c81dd28eb6da159fa0e6bc70e2d249fbce8
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