Image Classification
Transformers
PyTorch
ONNX
Safetensors
efficientnet
biology
efficientnet-b2
vision
Instructions to use dennisjooo/Birds-Classifier-EfficientNetB2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dennisjooo/Birds-Classifier-EfficientNetB2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dennisjooo/Birds-Classifier-EfficientNetB2") 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("dennisjooo/Birds-Classifier-EfficientNetB2") model = AutoModelForImageClassification.from_pretrained("dennisjooo/Birds-Classifier-EfficientNetB2") - Inference
- Notebooks
- Google Colab
- Kaggle
Delete onnx/quantize_config.json
Browse files
onnx/quantize_config.json
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