Instructions to use hf-tiny-model-private/tiny-random-VideoMAEForPreTraining with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-VideoMAEForPreTraining with Transformers:
# Load model directly from transformers import AutoImageProcessor, AutoModelForPreTraining processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-VideoMAEForPreTraining") model = AutoModelForPreTraining.from_pretrained("hf-tiny-model-private/tiny-random-VideoMAEForPreTraining") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2933abc1a80c0423d92b1351b0f1ecc3076f57e18e52742f8b9c0024cdb1c98
- Size of remote file:
- 28.7 MB
- SHA256:
- 2e3f4f24f7580ec1c088626f2585ba3068002109b3f87d3bfbfeb37e7027de89
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.