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:
- a44f4717fa9ddc905c33c63bd4d910f2cb9f93d57ab52a8da5eef8cf81dba447
- Size of remote file:
- 343 MB
- SHA256:
- a11a7cc19d243e779f0090ae83e2a2980772575f482e0f6d842acc9cca6fd636
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