Instructions to use microsoft/xclip-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/xclip-base-patch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="microsoft/xclip-base-patch32")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/xclip-base-patch32") model = AutoModel.from_pretrained("microsoft/xclip-base-patch32") - Notebooks
- Google Colab
- Kaggle
File size: 309 Bytes
3518578 e437ef9 3518578 e437ef9 3518578 e437ef9 3518578 c770c5b e437ef9 3518578 e437ef9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"do_center_crop": true,
"do_normalize": true,
"do_resize": true,
"feature_extractor_type": "VideoMAEFeatureExtractor",
"image_mean": [
0.485,
0.456,
0.406
],
"image_std": [
0.229,
0.224,
0.225
],
"processor_class": "XCLIPProcessor",
"resample": 2,
"size": 224
} |