SonySemiconductorSolutions / mct-model-optimizationLinks
Model Compression Toolkit (MCT) is an open source project for neural network model optimization under efficient, constrained hardware. This project provides researchers, developers, and engineers advanced quantization and compression tools for deploying state-of-the-art neural networks.
☆404Updated this week
Alternatives and similar repositories for mct-model-optimization
Users that are interested in mct-model-optimization are comparing it to the libraries listed below
Sorting:
- A set of simple tools for splitting, merging, OP deletion, size compression, rewriting attributes and constants, OP generation, change op…☆295Updated last year
- A parser, editor and profiler tool for ONNX models.☆442Updated last month
- ☆329Updated last year
- ☆206Updated 3 years ago
- OTOv1-v3, NeurIPS, ICLR, TMLR, DNN Training, Compression, Structured Pruning, Erasing Operators, CNN, Diffusion, LLM☆305Updated 9 months ago
- ☆151Updated 2 years ago
- [NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep L…☆583Updated last year
- ONNX Optimizer☆726Updated last week
- TFLite model analyzer & memory optimizer☆126Updated last year
- Count number of parameters / MACs / FLOPS for ONNX models.☆93Updated 8 months ago
- PyTorch Quantization Aware Training Example☆136Updated last year
- Neural Network Compression Framework for enhanced OpenVINO™ inference☆1,055Updated this week
- A code generator from ONNX to PyTorch code☆138Updated 2 years ago
- PyTorch implementation of Data Free Quantization Through Weight Equalization and Bias Correction.☆262Updated last year
- This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and…☆342Updated 2 years ago
- Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massiv…☆824Updated 2 weeks ago
- Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.☆442Updated 2 years ago
- Implementation of YOLOv9 QAT optimized for deployment on TensorRT platforms.☆115Updated 2 months ago
- μNAS is a neural architecture search (NAS) system that designs small-yet-powerful microcontroller-compatible neural networks.☆80Updated 4 years ago
- Inference of quantization aware trained networks using TensorRT☆82Updated 2 years ago
- Model Quantization Benchmark☆819Updated 2 months ago
- Common utilities for ONNX converters☆273Updated last week
- Transform ONNX model to PyTorch representation☆338Updated 7 months ago
- ONNX Script enables developers to naturally author ONNX functions and models using a subset of Python.☆360Updated this week
- Pytorch implementation of BRECQ, ICLR 2021☆276Updated 3 years ago
- On-Device Training Under 256KB Memory [NeurIPS'22]☆483Updated last year
- Quantization of Convolutional Neural networks.☆244Updated 11 months ago
- Inference Vision Transformer (ViT) in plain C/C++ with ggml☆287Updated last year
- Scailable ONNX python tools☆96Updated 8 months ago
- Conversion of PyTorch Models into TFLite☆385Updated 2 years ago