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:
- 9620673c2054694bf1b2df36591a48ae0b66143a03fed5ab43d533fb60ab0949
- Size of remote file:
- 8.63 kB
- SHA256:
- cdc9c84e37a07f3a936eacd9df31a6898f47dc7abbc04b0d4b58ed17882c3ce6
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