854c0518bc
This commit clarifies the usage of the Core ML encoder model in the whisper.obj and whisper.swiftui examples. Refs: https://github.com/ggerganov/whisper.cpp/issues/2783
whisper.objc
Minimal Obj-C application for automatic offline speech recognition. The inference runs locally, on-device.
https://user-images.githubusercontent.com/1991296/197385372-962a6dea-bca1-4d50-bf96-1d8c27b98c81.mp4
Real-time transcription demo:
https://user-images.githubusercontent.com/1991296/204126266-ce4177c6-6eca-4bd9-bca8-0e46d9da2364.mp4
Usage
This example uses the whisper.xcframework which needs to be built first using the following command:
./build-xcframework.sh
A model is also required to be downloaded and can be done using the following command:
./models/download-ggml-model.sh base.en
If you don't want to convert a Core ML model, you can skip this step by creating dummy model:
mkdir models/ggml-base.en-encoder.mlmodelc
Core ML
Follow the Core ML support section of readme to convert the model.
That is all the needs to be done to use the Core ML model in the app. The converted model is a
resource in the project and will be used if it is available. Note that the Core ML model is only
used for the encoder, the decoder which is in the ggml model is still required so both need to
be available.