Instructions to use Matthijs/snacks-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matthijs/snacks-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Matthijs/snacks-classifier") 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("Matthijs/snacks-classifier") model = AutoModelForImageClassification.from_pretrained("Matthijs/snacks-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 130 Bytes
8fac3d4 | 1 2 3 4 | `microsoft/swin-tiny-patch4-window7-224` fine-tuned on the `Matthijs/snacks` dataset.
Test set accuracy after 50 epochs: 0.9286.
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