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SparseML enables network sparsity with a few lines of code, through open-source libraries, to boost neural network inference performance.

SparseML allows you to create inference-optimized sparse models using state-of-the-art pruning and quantization algorithms. Models trained with SparseML can then be exported to ONNX and deployed with DeepSparse for GPU-class performance on CPU hardware.

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