Instructions to use hf-internal-testing/tiny-random-PvtV2Backbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PvtV2Backbone with Transformers:
# Load model directly from transformers import AutoImageProcessor, PvtV2Backbone processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-PvtV2Backbone") model = PvtV2Backbone.from_pretrained("hf-internal-testing/tiny-random-PvtV2Backbone") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fed7eb021d09a6f4abd5e77c06d9c448b935f0af23462c777d2cc31c9ba3ba24
- Size of remote file:
- 3.11 MB
- SHA256:
- 1871d1be259669543fc3b86693a66dc6fc3f9b4dd8154f9055a67c0dee1d1852
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.