Instructions to use Nadav/PretrainedPHD-v2-all-fonts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nadav/PretrainedPHD-v2-all-fonts with Transformers:
# Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("Nadav/PretrainedPHD-v2-all-fonts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fad524aaf139ea607d394391dc318885ddcf7668946637df912a3b0c101161c4
- Size of remote file:
- 5.55 kB
- SHA256:
- 53c18b4efeb50055b9df3de46e48e5ef92c97dea961e5c1e8f4076e024c3c1db
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.