Instructions to use mobilint/ShuffleNet_V2_X1_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/ShuffleNet_V2_X1_5 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="ShuffleNet_V2_X1_5", 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
Prepare board-specific Aries Vision artifacts 4cefa1c verified
Add library_name: mobilint to model card metadata 0fc4aa3 verified
Add ONNX model from torchvision f21044b verified
Update Mobilint logo URL in README f2329cb
Kanybek Asanbekov commited on
Move mxq and best_result to aries folder and update gitattributes e75489c
Kanybek Asanbekov commited on