ConvNext-Tiny-w8a8-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:w8a8 (8-bit weights, 8-bit activations)
Applicable Scenarios
- Medical Imaging
- Anomaly Detection
- Inventory Management
Supported Form Factors
- Phone
- Tablet
- IoT
Licenses
Source Model:BSD-3-CLAUSE
Deployable Model:AI Model Hub License
Tags
- quantized
Supported Devices
- QCS8250 (Proxy)
- QCS8550 (Proxy)
- RB5 (Proxy)
- SA7255P ADP
- SA8255 (Proxy)
- SA8295P ADP
- SA8650 (Proxy)
- SA8775P ADP
- Samsung Galaxy S21
- Samsung Galaxy S21 Ultra
- Samsung Galaxy S21+
- Samsung Galaxy S22 5G
- Samsung Galaxy S22 Ultra 5G
- Samsung Galaxy S22+ 5G
- Samsung Galaxy S23
- Samsung Galaxy S23 Ultra
- Samsung Galaxy S23+
- Samsung Galaxy S24
- Samsung Galaxy S24 Ultra
- Samsung Galaxy S24+
- Samsung Galaxy Tab S8
- Snapdragon 8 Elite QRD
- Snapdragon X Elite CRD
- Snapdragon X Plus 8-Core CRD
- Xiaomi 12
- Xiaomi 12 Pro
Supported Chipsets
- Qualcomm® QCS8250 (Proxy)
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® SA7255P
- Qualcomm® SA8255P (Proxy)
- Qualcomm® SA8295P
- Qualcomm® SA8650P (Proxy)
- Qualcomm® SA8775P
- Snapdragon® 8 Elite Mobile
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
- Snapdragon® X Elite
- Snapdragon® X Plus 8-Core
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