Instructions to use mobilint/EfficientNet_B5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/EfficientNet_B5 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="EfficientNet_B5", 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
14 days ago
-
Publish approved Variant MXQ
Verified signature60e6ee1
-
Prepare board-specific Aries Vision artifacts
Verified signature3034830 -
Prepare board-specific Aries Vision artifacts
Verified signature3cc1fa3
-
Restore library_name: mobilint for EfficientNet and GELAN model cards
Verified signature100c75e -
Adjust library_name metadata for model card
Verified signature5c0844d -
Add library_name: mobilint to model card metadata
Verified signaturef027156
-
Update ONNX model from torchvision
Verified signaturee12866d
-
Update Mobilint logo URL in README
Kanybek Asanbekovce1e48f
-
Fix .gitattributes order for *.mxq
Kanybek Asanbekovb992059 -
Add aries results and configure git lfs
Kanybek Asanbekov716bfa3
-
Create README.md
Verified signaturea1ca9ce -
initial commit
Verified signature04c0b4f