ConvNext-Tiny-w8a16-Quantized
Imagenet classifier and general purpose backbone.
ConvNextTiny is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.
Technical Details
Model checkpoint:Imagenet
Input resolution:224x224
Number of parameters:28.6M
Model size:28 MB
Precision:w8a16 (8-bit weights, 16-bit activations)
Applicable Scenarios
- Medical Imaging
- Anomaly Detection
- Inventory Management
Licenses
Source Model:BSD-3-CLAUSE
Deployable Model:AI Model Hub License
Tags
- quantizedA “quantized” model can run in low or mixed precision, which can substantially reduce inference latency.
Supported Compute Chipsets
- Snapdragon® X Elite