Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
huggingpics
Eval Results (legacy)
Instructions to use Bazaar/cv_level1_protected_animals_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bazaar/cv_level1_protected_animals_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Bazaar/cv_level1_protected_animals_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("Bazaar/cv_level1_protected_animals_classification") model = AutoModelForImageClassification.from_pretrained("Bazaar/cv_level1_protected_animals_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ea7877631627c61d0976c316cde2417c6f0fa7fbdd001f85748ac8d1640bf54
- Size of remote file:
- 343 MB
- SHA256:
- 37d6342c2ff8a610b661d650feb7648b65b2eb76803bc11c1ac06860cd0f70b4
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