Instructions to use pyronear/rexnet1_0x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pyronear/rexnet1_0x with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pyronear/rexnet1_0x") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pyronear/rexnet1_0x", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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docs: Updated dataset reference
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docs: Fixed README
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feat: Updated ONNX checkpoint
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feat: Updated ReXNet checkpoint
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feat: Added ONNX model
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docs: Updated README
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feat: Added config
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feat: Added Pytorch model
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initial commit
F-G Fernandez167e4a5