Instructions to use Nadav/PretrainedPHD-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nadav/PretrainedPHD-v3 with Transformers:
# Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("Nadav/PretrainedPHD-v3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0afefcbe3edd105c5e4bbeeec7ca26c1a9952e8aa757b7269c11266c5d041753
- Size of remote file:
- 5.55 kB
- SHA256:
- 92fe998606f51cfbdaeade2ff6ed2dfa530ab49cf5bec297af470359fd69c4bc
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