Instructions to use hf-internal-testing/tiny-random-levit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-levit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-levit") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-levit") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-levit") - Notebooks
- Google Colab
- Kaggle
File size: 268 Bytes
19bf21c | 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": "LevitFeatureExtractor",
"image_mean": [
0.485,
0.456,
0.406
],
"image_std": [
0.229,
0.224,
0.225
],
"resample": 3,
"size": 224
}
|