Instructions to use apjanco/candy-first with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apjanco/candy-first with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="apjanco/candy-first") 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("apjanco/candy-first") model = AutoModelForImageClassification.from_pretrained("apjanco/candy-first", device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 825d9e62e27c64199a77e2a3beeb3f014c814f3ba75e961e0bca63c6250ac347
- Size of remote file:
- 21.9 kB
- SHA256:
- 1880fe0d02e37356d6a20ced6614a78a26404a32d014d09c490a20e70b46b5d5
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