Congratulations on making it to the end of this short course. You learned about some common data types of representation in machine learning, such as integer and floating point, and how to load AI models using different data types. You also learned about the underlying concepts behind model quantization and how linear quantization works. You used the Quanto library to quantize any PyTorch model in 8-bit precision. Then, you learned about some applications of quantization on LLMs, such as the recent state-of-the-art methods for quantizing LLMs. With this knowledge in hand, you will be able to better understand the challenges of a model compression and select the best quantization techniques for your use case.💡 If you find this course helpful, maybe you can even share it with your friends 🤗.