Image Classification
Transformers
ONNX
Safetensors
English
efficientnet
biology
vision
Eval Results (legacy)
Instructions to use chriamue/bird-species-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chriamue/bird-species-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="chriamue/bird-species-classifier") 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("chriamue/bird-species-classifier") model = AutoModelForImageClassification.from_pretrained("chriamue/bird-species-classifier", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Upload Transformers-compatible ONNX weights (#1)
Browse files- Upload Transformers-compatible ONNX weights (a8c5612187548b7a81f4d7545bcbecc729a76d96)
- Delete onnx/model_quantized.onnx (9cbb59f37908008c58481bd70ff18b07f01162c9)
- Delete onnx/quantize_config.json (374a1c8f5d9344763ce250715c1f97c6d4c03f9a)
Co-authored-by: Joshua <Xenova@users.noreply.huggingface.co>
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