convnext_tiny¶
The convnext_tiny creates a ConvNeXt variant with a compact configuration, optimized for efficient computation and suitable for scenarios with limited computational resources. This model variant is designed with smaller depths and dimensions compared to the base ConvNeXt architecture.
Total Parameters: 28,589,128
Function Signature¶
@register_model
def convnext_tiny(num_classes: int = 1000, **kwargs) -> ConvNeXt
Parameters¶
num_classes (int, optional): The number of output classes for classification. Default is 1000.
kwargs (dict, optional): Additional keyword arguments for further customization of the ConvNeXt model.
Returns¶
ConvNeXt: An instance of the ConvNeXt model with a tiny configuration.
Examples¶
Basic Usage
from lucid.models import convnext_tiny
# Create a ConvNeXt-Tiny model with default 1000 classes
model = convnext_tiny(num_classes=1000)
# Input tensor with shape (1, 3, 224, 224)
input_ = lucid.random.randn(1, 3, 224, 224)
# Perform forward pass
output = model(input_)
print(output.shape) # Shape: (1, 1000)