Write a Python script to quantize an LLM for deployment on a Raspberry Pi

Question

Can you tell me how to Write a Python script to quantize an LLM for deployment on a Raspberry Pi.

Answer 1

You can quantize an LLM for deployment on a Raspberry Pi by leveraging torch.quantization to reduce model size and improve inference speed.

Here is the code snippet below:

In the above code, we are using the following key points:

• Dynamic quantization: Applies quantization to the linear layers of the model for memory and speed optimization

• Hugging Face Transformers: Loads a pre-trained language model and tokenizer

• Saving quantized models: The quantized model is saved for future use in a resource-constrained environment

Hence, this script efficiently quantizes an LLM, making it suitable for deployment in resource-constrained environments like the Raspberry Pi.