Instructions to use ltkien2003/vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltkien2003/vit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, ViViTForVideoClassification processor = AutoImageProcessor.from_pretrained("ltkien2003/vit") model = ViViTForVideoClassification.from_pretrained("ltkien2003/vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from ltkien2003/vit: direct link, hf CLI and curl.
- Browser
- Download file 401 Bytes
-
https://huggingface.co/ltkien2003/vit/resolve/refs%2Fpr%2F1/preprocessor_config.json
- Command line
-
hf download hf://ltkien2003/vit@refs/pr/1/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/ltkien2003/vit/resolve/refs%2Fpr%2F1/preprocessor_config.json
401 Bytes
| { | |
| "crop_size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "do_center_crop": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "ViViTImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00784313725490196, | |
| "size": { | |
| "shortest_edge": 224 | |
| } | |
| } | |