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| author | Konstantin <const@const.me> | 2023-01-16 15:19:41 +0100 |
|---|---|---|
| committer | Konstantin <const@const.me> | 2023-01-16 15:19:41 +0100 |
| commit | c838a2a24bc0f6c06c69044d074e15480fcf5596 (patch) | |
| tree | 8e22432aa6c04e68423cf6ac48cac2ea2a546409 /WhisperNet/Readme.md | |
| parent | d6504b5d59044e129160ed4f68ef290a4eb2f488 (diff) | |
Another readme for the nuget package
Diffstat (limited to 'WhisperNet/Readme.md')
| -rw-r--r-- | WhisperNet/Readme.md | 12 |
1 files changed, 12 insertions, 0 deletions
diff --git a/WhisperNet/Readme.md b/WhisperNet/Readme.md new file mode 100644 index 0000000..644384c --- /dev/null +++ b/WhisperNet/Readme.md @@ -0,0 +1,12 @@ +This library implements high-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model. + +The library requires a hardware GPU which supports Direct3D 11.0, a 64-bit Windows OS, only works within 64-bit processes, and requires a 64 bit CPU which supports SSE 4.1. + +The main entry point of the llibrary is `Whisper.Library` static class. +Call `loadModel` function from that class to load an ML model from a binary file. + +These binary files are available for free download on [Hugging Face]( https://huggingface.co/datasets/ggerganov/whisper.cpp). +I recommend `ggml-medium.bin` (1.42GB in size), because I’ve mostly tested the software with that model. + +Once the model is loaded, create a context by calling `createContext` extension method, +then use that object to transcribe or translate multimedia files or realtime audio captured from microphones.
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