inception_next_base

lucid.models.inception_next_base(num_classes: int = 1000, **kwargs) → InceptionNeXt

The inception_next_base function instantiates an InceptionNeXt-Base model, a standard variant of the InceptionNeXt architecture optimized for high accuracy and robust feature extraction in deep learning tasks.

Total Parameters: 86,748,840

Function Signature

@register_model
def inception_next_base(num_classes: int = 1000, **kwargs) -> InceptionNeXt

Parameters

  • num_classes (int, optional): Number of output classes for the final classification layer. Defaults to 1000.

  • kwargs (dict, optional): Additional arguments to customize the model configuration.

Returns

  • InceptionNeXt: An instance of the InceptionNeXt model configured as the small variant.

Example

from lucid.models import inception_next_base

# Instantiate InceptionNeXt-Small
model = inception_next_base(num_classes=1000)

# Forward pass with a random input
input_tensor = lucid.random.randn(1, 3, 224, 224)
output = model(input_tensor)
print(output.shape)  # Output shape: (1, 1000)