mobilenet_v4_conv_large¶

lucid.models.mobilenet_v4_conv_large(num_classes: int = 1000, **kwargs) → MobileNet_V4¶

Overview¶

The mobilenet_v4_conv_large function instantiates a MobileNet_V4 model configured for a large-scale convolutional variant. This variant is designed for higher accuracy requirements and is suited for devices with ample computational resources.

Total Parameters: 32,590,864

Function Signature¶

@register_model
def mobilenet_v4_conv_large(num_classes: int = 1000, **kwargs) -> MobileNet_V4

Parameters¶

num_classes (int, optional): Specifies the number of output classes. The default is 1000, which is standard for datasets such as ImageNet.
**kwargs (dict): Additional keyword arguments to customize the model configuration. These can be used to modify default settings and adapt the architecture for specific tasks.

Usage Example¶

>>> import lucid.models as models
>>> model = models.mobilenet_v4_conv_large(num_classes=1000)
>>> print(model)

Details¶

The mobilenet_v4_conv_large function leverages a large convolutional configuration to boost model accuracy by increasing the depth and capacity of the network.

Note

For applications where computational resources are limited, consider using the smaller or medium variants.