Instructions to use anum231/class2_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anum231/class2_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="anum231/class2_v1") 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("anum231/class2_v1") model = AutoModelForImageClassification.from_pretrained("anum231/class2_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35d742b6c1ca278a4ba62f3ccc5d5867638be6ad209eee1732b5d4430e3b6b0f
- Size of remote file:
- 343 MB
- SHA256:
- b3f20366a6f0521fdb7cec2cddb38db105cd4c16318d92bcf755a252e0a86f71
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