Instructions to use mrsarthakgupta/univdetectpush with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrsarthakgupta/univdetectpush with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="mrsarthakgupta/univdetectpush") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForZeroShotImageClassification processor = AutoImageProcessor.from_pretrained("mrsarthakgupta/univdetectpush") model = AutoModelForZeroShotImageClassification.from_pretrained("mrsarthakgupta/univdetectpush", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 317 Bytes
273defe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.48, 0.46, 0.41
],
"image_processor_type": "ViTFeatureExtractor",
"image_std": [
0.27, 0.26, 0.28
],
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 224,
"width": 224
}
}
|