Instructions to use google/vivit-b-16x2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vivit-b-16x2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="google/vivit-b-16x2")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("google/vivit-b-16x2") model = AutoModelForVideoClassification.from_pretrained("google/vivit-b-16x2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 430 Bytes
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"crop_size": {
"height": 224,
"width": 224
},
"do_center_crop": true,
"do_normalize": false,
"do_rescale": true,
"do_resize": true,
"do_zero_centering": 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": 256
}
}
|