SparseML is an optimization toolkit for training and deploying deep learning models using sparsification techniques like pruning and quantization to improve efficiency.

Features

  • Supports pruning, quantization, and distillation for model compression
  • Works with PyTorch and TensorFlow models
  • Enables efficient inference on CPUs without GPUs
  • Provides pre-optimized recipes for popular deep learning architectures
  • Reduces model size while maintaining accuracy
  • Compatible with DeepSparse for optimized execution

Project Samples

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License

Apache License V2.0

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Natural Language Processing (NLP) Tool, Python LLM Inference Tool

Registered

2025-01-22