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Hi, I tried the yolov5 tutorials with --recipe = yolov5s.pruned_quantized.md
The QAT works as I can see fake quantized modules in netron but the number of parameters remain unchanged.
Are there any…
MrOCW updated
2 years ago
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**Is your feature request related to a problem? Please describe.**
Some ML models are optimized for certain architectures. It would be nice to get hardware with `avx2` or `avx512` capabilities in sma…
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Hi, thanks for the well-organized repository.
I've been following the classification tutorial that prunes and finetunes ResNet50 for Imagenette. The pruning seemed to have worked and both PTH and O…
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Hi,
Quantization is not available in the UI, could you provide an approximate ETA? is there a recommended course of action for performing pruning with UI and quantization by other means?
Thanks!
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Hello,
I have trained several pruned models and saved the weights (using other pruning methods) and converted the saved models to onnx (using torch). I'm interested in comparing their inference time…
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Hi, I test yolov5s model in ubuntu 16.04 but the speed is very slow as below figure. It warns that VNNI instructions not detected, quantization speedup not well supported. What't the problem and how s…
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It is really nice to have comparison of INT8 Performance - without Pruning vs with Pruning
Can that be included in the [Blog Page](https://neuralmagic.com/blog/benchmark-resnet50-with-deepsparse/) ?…
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I followed this：
https://github.com/neuralmagic/sparseml/blob/main/integrations/ultralytics-yolov5/tutorials/sparsifying_yolov5_using_recipes.md
and I get a big model more than 80M size.
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Hi, I wonder if sparseml provides tools to calculate the memory consumption per sample? I mean the feature map size in every layer. For the standard feature map size calculation I know there are some …
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Hi, I tried to run the following codes and it seems that it could run smoothly on my mac/terminal, but always died if I run in jupyter notebook:
```
from sparseml.pytorch.models import ModelRegistry…