mit-han-lab / tinyml
☆854Updated 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…☆539Updated 11 months ago
- [NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep L…☆844Updated 3 months ago
- MLPerf™ Tiny is an ML benchmark suite for extremely low-power systems such as microcontrollers☆390Updated this week
- On-Device Training Under 256KB Memory [NeurIPS'22]☆464Updated 11 months ago
- This is a list of interesting papers and projects about TinyML.☆845Updated 2 months ago
- vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers☆587Updated 2 years ago
- ☆221Updated last year
- CMSIS-NN Library☆253Updated last month
- [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment☆1,903Updated last year
- Arm NN ML Software. The code here is a read-only mirror of https://review.mlplatform.org/admin/repos/ml/armnn☆1,245Updated this week
- Arm Machine Learning tutorials and examples☆448Updated 3 months ago
- Brevitas: neural network quantization in PyTorch☆1,278Updated this week
- μNAS is a neural architecture search (NAS) system that designs small-yet-powerful microcontroller-compatible neural networks.☆79Updated 4 years ago
- A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.☆346Updated 7 months ago
- Embedded and mobile deep learning research resources☆746Updated 2 years ago
- AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.☆2,255Updated this week
- A curated list of resources for embedded AI☆407Updated last month
- PyTorch library to facilitate development and standardized evaluation of neural network pruning methods.☆428Updated last year
- Model Compression Toolkit (MCT) is an open source project for neural network model optimization under efficient, constrained hardware. Th…☆376Updated this week
- [CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision☆380Updated 4 years ago
- PyTorch implementation for the APoT quantization (ICLR 2020)☆271Updated 3 months ago
- Model Quantization Benchmark☆793Updated 2 months ago
- TFLite model analyzer & memory optimizer☆124Updated last year
- Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.☆429Updated last year
- Awesome machine learning model compression research papers, quantization, tools, and learning material.☆507Updated 6 months ago
- A simple network quantization demo using pytorch from scratch.☆522Updated last year
- [CVPR'20] ZeroQ: A Novel Zero Shot Quantization Framework☆277Updated last year
- Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digit…☆2,148Updated this week
- TinyML Cookbook, published by Packt☆262Updated last year
- QKeras: a quantization deep learning library for Tensorflow Keras☆560Updated last month