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:
- 23082b051fb16cc4d05c36fb7a1599500d65c51380c0fef2871ea56e31f3255b
- Size of remote file:
- 121 kB
- SHA256:
- 7d79418ec2ae1a039c5553f24ebe911f77f8389c1547bd3ef4b6ec71e4896585
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