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Minor updates
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README.md
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README.md
@ -7,13 +7,12 @@ High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisp
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- Mixed F16 / F32 precision
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- Low memory usage (Flash Attention + Flash Forward)
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- Zero memory allocations at runtime
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- Runs on the CPU (Mac and Linux)
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- Runs on the CPU
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- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/whisper.h)
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- Supported platforms: Linux, Mac OS (Intel and Arm), Raspberry Pi, Android
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Incoming features:
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- [Realtime audio input transcription](https://github.com/ggerganov/whisper.cpp/issues/10#issuecomment-1264665959)
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- [Raspberry Pi support](https://github.com/ggerganov/whisper.cpp/issues/7)
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- [Android support](https://github.com/ggerganov/whisper.cpp/issues/8)
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## Usage
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@ -220,10 +219,16 @@ $ ./stream -m models/ggml-small.en.bin -t 8
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https://user-images.githubusercontent.com/1991296/193465125-c163d304-64f6-4f5d-83e5-72239c9a203e.mp4
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## Implementation details
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- The core tensor operations are implemented in C (`ggml.h` / `ggml.c`)
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- The high-level C-style API is implemented in C++ (`whisper.h` / `whisper.cpp`)
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- Simple usage is demonstrated in `main.cpp`
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- Sample real-time audio transcription from the microphone is demonstrated in `stream.cpp`
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## Limitations
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- Very basic greedy sampling scheme - always pick up the top token
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- Only 16-bit WAV at 16 kHz is supported
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- Very basic greedy sampling scheme - always pick up the top token. You can implement your own strategy
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- Inference only
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- No GPU support
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@ -265,6 +265,11 @@ int main(int argc, char ** argv) {
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wparams.print_progress = false;
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wparams.print_special_tokens = params.print_special_tokens;
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wparams.print_realtime = false;
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wparams.print_timestamps = !params.no_timestamps;
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wparams.translate = params.translate;
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wparams.language = params.language.c_str();
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wparams.n_threads = params.n_threads;
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if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
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fprintf(stderr, "%s: failed to process audio\n", argv[0]);
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