Skip to content

v0.8.0
Compare
Choose a tag to compare
@bhushan23 bhushan23 released this 12 Jun 16:58
· 4 commits to main since this release
v0.8.0
a1c0616

New Additions

  • All ImageNet based models now have evaluate.py files: You can now do a full numerical accuracy evaluation on-device through AI Hub.
  • Select models now have labels.txt files: With this feature, we are adding the classification labels for models so you can build end to end applications more easily.
  • When exporting quantized ONNX models, the inputs and outputs are now quantized automatically by default

Quality Improvements & Bug Fixes

  • Performance improvement for the "yolov8seg" and "sesr_m5_quantized" models by changing the output shape to "channel last"
  • Align printed memory in export with numbers from hub web page
  • Added missing requirements for yolonas and yolonas-quantized

Performance Numbers

  • Updated existing numbers to reflect benchmarks from latest AI Hub toolchain
  • Updated llama2 numbers for X Elite
Assets 2
Loading