quic / aimetLinks
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
☆2,471Updated this week
Alternatives and similar repositories for aimet
Users that are interested in aimet are comparing it to the libraries listed below
Sorting:
- ☆335Updated last year
- Simplify your onnx model☆4,209Updated last month
- PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT☆2,873Updated last week
- A tool to modify ONNX models in a visualization fashion, based on Netron and Flask.☆1,563Updated 7 months ago
- Neural Network Compression Framework for enhanced OpenVINO™ inference☆1,087Updated last week
- SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX R…☆2,511Updated this week
- [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment☆1,930Updated last year
- ONNX Optimizer☆764Updated 2 weeks ago
- Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX☆2,478Updated last month
- TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.☆851Updated 2 months ago
- Tensorflow Backend for ONNX☆1,325Updated last year
- Model Quantization Benchmark☆843Updated 6 months ago
- A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are co…☆2,241Updated 7 months ago
- ONNX-TensorRT: TensorRT backend for ONNX☆3,156Updated last month
- A parser, editor and profiler tool for ONNX models.☆458Updated 2 months ago
- A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. …☆1,443Updated last week
- Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distille…☆4,401Updated 2 years ago
- Reference implementations of MLPerf™ inference benchmarks☆1,475Updated this week
- High-efficiency floating-point neural network inference operators for mobile, server, and Web☆2,129Updated this week
- A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.☆1,557Updated this week
- Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massiv…☆867Updated 3 months ago
- Convert ONNX models to PyTorch.☆705Updated last week
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,525Updated last year
- Bolt is a deep learning library with high performance and heterogeneous flexibility.☆952Updated 6 months ago
- ☆985Updated last year
- Brevitas: neural network quantization in PyTorch☆1,401Updated this week
- [CVPR 2023] DepGraph: Towards Any Structural Pruning; LLMs, Vision Foundation Models, etc.☆3,151Updated last month
- Quantized Neural Network PACKage - mobile-optimized implementation of quantized neural network operators☆1,546Updated 6 years ago
- PPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.☆1,754Updated last year
- Tutorials for creating and using ONNX models☆3,613Updated last year