Instructions to use tdros/zoalearn2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tdros/zoalearn2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tdros/zoalearn2") 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("tdros/zoalearn2") model = AutoModelForImageClassification.from_pretrained("tdros/zoalearn2") - Notebooks
- Google Colab
- Kaggle
zoalearn2
zoalearn2 is google/vit-base-patch16-224-in21k fine-tuned to classify 32 of the most popular coral speices.
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Evaluation results
- Accuracyself-reported0.810