Instructions to use mobilint/CoAtNet_1_RW_224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/CoAtNet_1_RW_224 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="CoAtNet_1_RW_224", model_type="DEFAULT", model_path="", core_mode="global8", ) try: image = model.preprocess("path/to/image.jpg") output = model(image) result = model.postprocess(output) finally: model.dispose() - Notebooks
- Google Colab
- Kaggle
Commit History
3 days ago
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Publish approved Variant MXQ
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13 days ago
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Publish approved Variant MXQ
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Prepare board-specific Aries Vision artifacts
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Prepare board-specific Aries Vision artifacts
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Add library_name: mobilint to model card metadata
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Add ONNX model from timm
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Update Mobilint logo URL in README
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Add mxq and best_result.json to aries folder
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feat: add CoAtNet_1_RW_224 mxq model files and configure git LFS tracking for mxq extension.
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Update README.md
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initial commit
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