sipeed/TinyMaix
TinyMaix is a C library for running neural network inference on microcontrollers with less than 3KB of code and support for 48 different chips.
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TinyMaix is a tiny inference library for microcontrollers (TinyML) that converts and runs neural network models in INT8/FP32/FP16 formats. The core library is under 400 lines of code with a .text section under 3KB, enabling even ATmega328-class devices to run MNIST inference. It supports multiple architecture accelerations including ARM SIMD/NEON, RISC-V, CSKYV2, and X86 SSE2, and provides simple APIs to load and run models on resource-constrained hardware.
Frequently asked
- What is sipeed/TinyMaix?
- TinyMaix is a C library for running neural network inference on microcontrollers with less than 3KB of code and support for 48 different chips.
- Is TinyMaix open source?
- Yes — sipeed/TinyMaix is open source, released under the Apache-2.0 license.
- What language is TinyMaix written in?
- sipeed/TinyMaix is primarily written in C.
- How popular is TinyMaix?
- sipeed/TinyMaix has 1.1k stars on GitHub.
- Where can I find TinyMaix?
- sipeed/TinyMaix is on GitHub at https://github.com/sipeed/TinyMaix.