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:
- 50b90133e5fa102777a904eedf4f569f5bd6453c0fbc307f0afee9b4d0076675
- Size of remote file:
- 3.11 MB
- SHA256:
- 4edbf68c127f023c6df40540b4d74f30a800a781bcbab3f1f4df46592c36e1c3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.