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
| { | |
| "_valid_processor_keys": [ | |
| "images", | |
| "do_resize", | |
| "size", | |
| "resample", | |
| "do_rescale", | |
| "rescale_factor", | |
| "do_normalize", | |
| "image_mean", | |
| "image_std", | |
| "return_tensors", | |
| "data_format", | |
| "input_data_format" | |
| ], | |
| "crop_size": [ | |
| 64, | |
| 64 | |
| ], | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "PvtImageProcessor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 64, | |
| "width": 64 | |
| } | |
| } | |