Welcome to AI Model Efficiency Toolkit API Docs!

AI Model Efficiency Toolkit (AIMET) is a software toolkit that enables users to compress and quantize ML models. The resulting models returned by AIMET can be further trained (or fine-tuned) to dramatically improve accuracy lost due to quantization and compression.

AIMET is designed to work generically on any user-provided model. At present, AIMET supports TensorFlow, Keras, PyTorch, and ONNX frameworks.

Please follow the links below to see AIMET APIs for either PyTorch, TensorFlow, or ONNX.

• AIMET APIs for PyTorch
  • PyTorch Model Quantization API
  • PyTorch Model Compression API
  • PyTorch Model Visualization API for Compression
  • PyTorch Model Visualization API for Quantization
  • PyTorch Debug API

• AIMET APIs for TensorFlow
  • TensorFlow Model Quantization API
  • TensorFlow Debug API
  • TensorFlow Model Compression API

• AIMET APIs for ONNX
  • ONNX Model Quantization API
  • ONNX Debug API

Note

This documentation is auto-generated from the AIMET codebase using Sphinx

Indices and tables

• Index

• Module Index

• Search Page