Instructions to use pyronear/rexnet1_3x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pyronear/rexnet1_3x with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pyronear/rexnet1_3x") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pyronear/rexnet1_3x", device_map="auto") - Notebooks
- Google Colab
- Kaggle
F-G Fernandez commited on
Commit ·
ab8513c
1
Parent(s): 2ad4b68
feat: Updated model checkpoint
Browse files- config.json +1 -1
- model.onnx +2 -2
- pytorch_model.bin +2 -2
config.json
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{"mean": [0.485, 0.456, 0.406], "std": [0.229, 0.224, 0.225], "arch": "rexnet1_3x", "interpolation": "bilinear", "input_shape": [3,
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{"mean": [0.485, 0.456, 0.406], "std": [0.229, 0.224, 0.225], "arch": "rexnet1_3x", "interpolation": "bilinear", "input_shape": [3, 256, 384], "classes": ["Wildfire"]}
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model.onnx
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pytorch_model.bin
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