secondstate/burn-whisper repository overview

# Put the audio file you want to handle in $(pwd)
# The `audio16k.wav` is used in the following example.
docker run \
  --runtime=io.containerd.wasmedge.v1 \
  --platform=wasi/wasm \
  -v $(pwd):/resource \
  --env WASMEDGE_WASINN_PRELOAD=default:Burn:GPU:/tiny_en.mpk:/tiny_en.cfg:/tokenizer.json:en \
  whisper:latest /resource/audio16k.wav default

Loaded graph into wasi-nn with ID: 0
Created wasi-nn execution context with ID: 0
Loading waveform...
Executed audio to text converter.
Text:  Hello, I am the whisper machine learning model. If you see this as text then I am working properly.