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:
- 1c5e1007e182bc23ddc6dd6c0f4cb177e8559f3abedfc9263d1c77908ba02524
- Size of remote file:
- 28.4 kB
- SHA256:
- dc3ed45e305250a06e31aa2e8f95ee1b36cc83f58564df56be8c51ee0d2d2026
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