juntao

name: github pages
on:
  push:
    branches:
      - master
jobs:
  deploy:
    runs-on: ubuntu-18.04
    steps:
      - uses: actions/checkout@v1  # v2 does not have submodules option now

juntao

// Load the model data from a file
let model_data: &[u8] = include_bytes!("lite-model_aiy_vision_classifier_food_V1_1.tflite");

// Read the input image data from Tencent Cloud's API gateway
let mut buffer = String::new();
io::stdin().read_to_string(&mut buffer).expect("Error reading from STDIN");
let obj: FaasInput = serde_json::from_str(&buffer).unwrap();
let img_buf = base64::decode_config(&(obj.body), base64::STANDARD).unwrap();

// Resize the image to the size needed by the Tensorflow model

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let labels = include_str!("aiy_food_V1_labelmap.txt");

let mut i = 0;
let mut max_index: i32 = -1;
let mut max_value: u8 = 0;
while i < res_vec.len() {
    let cur = res_vec[i];
    if cur > max_value {
        max_value = cur;
        max_index = i as i32;

juntao

Setup CUDA on AWS EC2 Instance

This tutorial is based on this AWS tutorial. In this tutorial, we will install Nvidia driver on AWS EC2 instance and compile and run llama.cpp on it.

Create an AWS EC2 instance

Here we use g5.4xlarge instance with Ubuntu 22.04 AMI, which use Nvidia A10G GPU.

Install Nvidia driver