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:
- 6879d5a046b00b8d5950ffea4d9afd11554ef56c6fccf9f4057e3232328644fb
- Size of remote file:
- 57.1 kB
- SHA256:
- 769fd12294924904ae172a416591c6bc36b04a6a4a328bbc79f7b1b086c322e3
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