Whisper on EC2 jumpstart

Introduction:

Through Cloudformation on AWS, create a VPC network environment with one click, and deploy an Whisper model within it to run UI based on Streamlit.

Project Includes:

• ui.py: A Python application based on Streamlit, providing a simple Web interface to use the whisperx model, converting audio to txt.

• whisper.yaml: An AWS Cloudformation YAML file that automatically provides AWS G4 instances and installs Nvidia drivers and whisperx related libraries to run ui.py.

Install guide：

• Accept the user agreement for the following models (click through the links bellow and accept the terms):

  1. Segmentation
  2. Voice Activity Detection (VAD)
  3. Speaker Diarization.

• Create life EC2 keypair through AWS Console.

  

• Find the ami id through the console interface:

  

• Create stack in cloudformation console

  

• Set parameter of the project

  

• Output IP address after installation:

  

• Wait around 10 minutes for the EC2 instance to initialize the environment and install the diffusion library.

• Connect to the EC2 instance via SSH and run

tail -f /var/log/cloud-init-output.log

to check the installation progress.

• Connect to the EC2 instance via SSH and

run nvidia-smi

You should see the NVIDIA system management interface

• Navigate to the whisper directory. The python3 ui.py service is already running by default. You can stop the service with sudo systemctl stop myapp.service.

• Access the output ip address

http://{ip_address}:8501

to see the UI.

• Stop the background service with

 sudo systemctl stop whisper.service

• Start the background service with

 sudo systemctl start whisper.service

UI Guide:

• Auto download and transcribe youtube to text

  

• Upload mp3 and transcribe to text