Instructions to use ArrayDice/car_orientation_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArrayDice/car_orientation_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ArrayDice/car_orientation_classification") 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("ArrayDice/car_orientation_classification") model = AutoModelForImageClassification.from_pretrained("ArrayDice/car_orientation_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32c63c3e3a6422e6b8bd62e71526cd64dda32129179a5178ae032c3179a71296
- Size of remote file:
- 5.11 kB
- SHA256:
- be1d791fbf6e93a0a8d4e24318569e74abae013964606e74252d23f192db97dd
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