Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
huggingpics
Eval Results (legacy)
Instructions to use Bazaar/cv_bird_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bazaar/cv_bird_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Bazaar/cv_bird_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_bird_classification") model = AutoModelForImageClassification.from_pretrained("Bazaar/cv_bird_classification") - Notebooks
- Google Colab
- Kaggle
cv_bird_classification
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
Black footed Albatross
Brewer Blackbird
Crested Auklet
Groove billed Ani
Laysan Albatross
Least Auklet
Parakeet Auklet
Red winged Blackbird
Rhinoceros Auklet
Sooty Albatross
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Evaluation results
- Accuracyself-reported0.877









