Instructions to use yangswei/snacks_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangswei/snacks_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="yangswei/snacks_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("yangswei/snacks_classification") model = AutoModelForImageClassification.from_pretrained("yangswei/snacks_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc5fb9a8cf378018ab0a8dac35184bfd46baabe51fa8f6a22ffe4d78f0ab696e
- Size of remote file:
- 4.73 kB
- SHA256:
- de0622f286f4e211e4be6b4058b54fef84b6060adb351d8ba1f9ef927fcbbd14
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