What you've learned
You should now know how to:
- Download the Meta Llama 3.1 model from the Meta Hugging Face repository.
- 4-bit quantize the model using optimized INT4 KleidiAI Kernels for PyTorch.
- Run an LLM inference using PyTorch on an Arm-based CPU.
- Expose an LLM inference as a browser application with Streamlit as the frontend and Torchchat framework in PyTorch as the LLM backend server.
- Measure performance metrics of the LLM inference running on an Arm-based CPU.