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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download images/Grus_antigone.jpg from Bazaar/cv_level1_protected_animals_classification: direct link, hf CLI and curl.
- Browser
- Download file 50.2 kB
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https://huggingface.co/Bazaar/cv_level1_protected_animals_classification/resolve/main/images/Grus_antigone.jpg
- Command line
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hf download hf://Bazaar/cv_level1_protected_animals_classification/images/Grus_antigone.jpg
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curl -L -o Grus_antigone.jpg https://huggingface.co/Bazaar/cv_level1_protected_animals_classification/resolve/main/images/Grus_antigone.jpg
50.2 kB
