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:
- d046d0201e231804ac30ddadcfa1a81224c6e573cf7157ec88452b580ac321e1
- Size of remote file:
- 3.11 MB
- SHA256:
- 7439fd8a3e6633944ec1a58534ffccdae8b8b32f754bd062f3c2b07ce046da74
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.