Instructions to use Nadav/pixel-intermediate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nadav/pixel-intermediate with Transformers:
# Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("Nadav/pixel-intermediate", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e0f0e14ea24c4cbb5d21256cd47be434f252a69ee46336d9707ecb43d620ac9
- Size of remote file:
- 449 MB
- SHA256:
- 207b689dc20acc0d2a0e375eb166e925399ce7d85ed5eab0492acb43daf3c3d7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.