Sparsity-aware deep learning inference runtime for CPUs

By the end of this post, you will learn how to: Train a SOTA YOLOv5 model on your own data. Sparsify the model using SparseML quantization aware training, sparse transfer learning, and one-shot quantization. Export the sparsified model and run it using the DeepSparse engine at insane speeds. P/S: The end result - YOLOv5 on CPU at 180+ FPS using on

Hierarchical Models for Learning Features from Images and Videos

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[TMI 2026] DeepSparse: A Foundation Model for Sparse-View CBCT Reconstruction

C++ implementation of YOLO-NAS using DeepSparse

AISTATS Submission code

CPU inference using DeepSparse

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(WIP) DeepSparse Engine vs OpenVINO Inference Benchmarking

Example of DeepSparse Engine running with Milvus

In this repository we try to combine Sparse Grids and Tensorflow to improve on existing Machine Learning approaches. Here we combine the efficient discretization of Sparse Grids and the strengths of Neural Networks.

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DeepSparse Server Running BERT

Comparing deepsparse and openvino

Benchmarking YOLOv5 on DeepSparse

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Example using DeepSparse with Kubernetes

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example for deepsparse llm in basic server

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Examples using deepsparse engine and sparseml libraries

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Example project serving deepsparse and llama2 7b over fastapi

in this repo we will inference using deepsparse library from neural magic

Library to test performance of deepsparse vs onnx vs openvino

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Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging