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yum-archive/TaSTT-Whisper

High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model

git clone https://git.yummers.dev/yum-archive/TaSTT-Whisper

KonstantinAnother readme for the nuget packagec838a2a2023-01-16

renderedcode

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. 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.

1This library implements high-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model.
2
3The 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.
4
5The main entry point of the llibrary is `Whisper.Library` static class.
6Call `loadModel` function from that class to load an ML model from a binary file.
7
8These binary files are available for free download on [Hugging Face]( https://huggingface.co/datasets/ggerganov/whisper.cpp).
9I recommend `ggml-medium.bin` (1.42GB in size), because I’ve mostly tested the software with that model.
10
11Once the model is loaded, create a context by calling `createContext` extension method,
12then use that object to transcribe or translate multimedia files or realtime audio captured from microphones.