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:
- 5a0b609e1e4d6cff06700a68fe43039906390955b7d857c1f20d140d1ed6db59
- Size of remote file:
- 30.9 kB
- SHA256:
- a043806704dbc2cc6a6144cdf9b6473f3736cc281f68dd1f97958efa744c8f71
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