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:
- 69cb0a048ec07048739925f32fffa5674018680e7fbd6d09b9819a1a88bdb305
- Size of remote file:
- 3.11 MB
- SHA256:
- 62a40a331a2236ad2d43d27c09c659fdc50d0a238c6e1028a805e89058822d04
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.