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:
- 401f722714105c5d8848a60644ca1d595574ff3a80bd64c3ea6cc0343c1d0c4d
- Size of remote file:
- 13 kB
- SHA256:
- fe293860230ac714b52b4cd71b88d1c967f6dc0c42516a05c80f227fe8f00d83
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