Update readme.md

Author: cpldcpu

readme.md

@@ -2,6 +2,8 @@
 
 **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*.
 
+The training pipeline is based in PyTorch and should run anywhere. The inference engine is implemented in Ansi-C and can be easily ported to any Microcontroller.
+
 **You can find a detailed report on the project in the `docs/` directory [here](docs/documentation.md).**
 
 <div align="center">