Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use miittnnss/pet-classifier-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miittnnss/pet-classifier-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="miittnnss/pet-classifier-v2") 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("miittnnss/pet-classifier-v2") model = AutoModelForImageClassification.from_pretrained("miittnnss/pet-classifier-v2") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- fb7892ca94f4a2a31c71db0d0f5b96e014d719354bc7496a0ab28f8ecbb9a26b
- Size of remote file:
- 30.6 kB
- SHA256:
- 09ded2d90aff62fea2ec4b72297bf66519b28b5f414c93483712ebddac87b6d6
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