mit-han-lab / tinyml
☆894Updated last year
Alternatives and similar repositories for tinyml:
Users that are interested in tinyml are comparing it to the libraries listed below
- [NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep L…☆563Updated last year
- [NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep L…☆864Updated 5 months ago
- On-Device Training Under 256KB Memory [NeurIPS'22]☆475Updated last year
- [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment☆1,913Updated last year
- MLPerf™ Tiny is an ML benchmark suite for extremely low-power systems such as microcontrollers☆403Updated last week
- Model Compression Toolkit (MCT) is an open source project for neural network model optimization under efficient, constrained hardware. Th…☆394Updated this week
- Arm Machine Learning tutorials and examples☆455Updated 5 months ago
- ☆224Updated 2 years ago
- CMSIS-NN Library☆269Updated 2 weeks ago
- This is a list of interesting papers and projects about TinyML.☆864Updated 4 months ago
- A curated list of resources for embedded AI☆418Updated last month
- [CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision☆384Updated 4 years ago
- Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.☆432Updated last year
- TinyML Cookbook, published by Packt☆273Updated last year
- [ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices☆441Updated last year
- μNAS is a neural architecture search (NAS) system that designs small-yet-powerful microcontroller-compatible neural networks.☆79Updated 4 years ago
- Arm NN ML Software. The code here is a read-only mirror of https://review.mlplatform.org/admin/repos/ml/armnn☆1,257Updated this week
- A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.☆350Updated 9 months ago
- ☆244Updated last year
- AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.☆2,293Updated this week
- Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digit…☆2,231Updated 2 weeks ago
- A curated list of awesome edge machine learning resources, including research papers, inference engines, challenges, books, meetups and o…☆261Updated 2 years ago
- ☆322Updated last year
- PyTorch implementation for the APoT quantization (ICLR 2020)☆273Updated 5 months ago
- PyTorch library to facilitate development and standardized evaluation of neural network pruning methods.☆429Updated last year
- Awesome machine learning model compression research papers, quantization, tools, and learning material.☆515Updated 7 months ago
- [CVPR'20] ZeroQ: A Novel Zero Shot Quantization Framework☆278Updated last year
- Collection of recent methods on (deep) neural network compression and acceleration.☆946Updated last month
- Brevitas: neural network quantization in PyTorch☆1,304Updated this week
- Supporting PyTorch models with the Google AI Edge TFLite runtime.☆569Updated this week