qualcomm/aimet
Qualcomm's toolkit for quantizing and compressing trained neural network models to reduce memory footprint and compute load.
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AIMET provides post-training and quantization-aware fine-tuning techniques to minimize accuracy loss when compressing deep learning models. It supports models from ONNX and PyTorch frameworks and is designed to facilitate efficient deployment on resource-constrained edge devices like mobile phones and laptops.
Frequently asked
- What is qualcomm/aimet?
- Qualcomm's toolkit for quantizing and compressing trained neural network models to reduce memory footprint and compute load.
- Is aimet open source?
- Yes — qualcomm/aimet is an open-source project tracked on heatdrop.
- What language is aimet written in?
- qualcomm/aimet is primarily written in Python.
- How popular is aimet?
- qualcomm/aimet has 2.7k stars on GitHub.
- Where can I find aimet?
- qualcomm/aimet is on GitHub at https://github.com/qualcomm/aimet.