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:
- 748a4a1878eb655c78fa903ff89e556530c6fbc93961d3ed4b0ed17ea4a1c68f
- Size of remote file:
- 5.55 kB
- SHA256:
- 3ffbace6af33e15cfb1f1ee5cd7d43fec11995860b2c004e4c591e320c40cf9b
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