Instructions to use kayleenp/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kayleenp/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kayleenp/image_classification") 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("kayleenp/image_classification") model = AutoModelForImageClassification.from_pretrained("kayleenp/image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4e13a4667f6b5f28666f41215285ad0290b2cb16bb20ac79430283430e814f8
- Size of remote file:
- 343 MB
- SHA256:
- aebaac5a00da4e06c15c215f988cee12c3eae18c940b03ed239d51911c87e75d
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