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torchvision/convnext_base

Embedl-optimized
ConvNeXt Base architecture graph
ConvNeXt Base architecture graph
  • torchvision/convnext_base
  • INT8
  • L4
Labels
  • Image
  • Classification
Build
Embedl-optimized
Precision
INT8
Runtime
TensorRT with Embedl optimizations
Run ConvNeXt Base on L4

ConvNeXt Base is an image classifier from torchvision. It labels an image with one of the 1,000 ImageNet classes.

Methodology

  • Latency: on the NVIDIA L4, batch 1, median GPU compute time (no copies to and from the GPU), from the build's own benchmark.
  • Accuracy: the ImageNet-1k validation split, 50,000 images, from the build's own validation on the NVIDIA L4.
  • Baseline TensorRT: the original model in FP16 on upstream TensorRT, same settings, same device. Not measured yet.
  • Build: Embedl Deploy quantization (INT8 weights per channel and activations), calibrated with ImageNetCalibDataset, 5000 batches of 1, exported to ONNX and compiled with Embedl's TensorRT transforms.