**BitNetMCU** is a project focused on the training and inference of low-bit quantized neural networks, specifically designed to run efficiently on low-end RISC-V microcontrollers like the CH32V003. Quantization aware training (QAT) and finetuning of model structure and inference code allowed *surpassing 99% Test accuracy on a 16x16 MNIST dataset without using multiplication instructions and in only 2kb of RAM and 16kb of Flash*.
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