diff --git a/README.md b/README.md index f87bcf17..3ae9e73a 100644 --- a/README.md +++ b/README.md @@ -12,17 +12,17 @@ Stable: [v1.7.1](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.7.1) / High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model: - Plain C/C++ implementation without dependencies -- Apple Silicon first-class citizen - optimized via ARM NEON, Accelerate framework, Metal and [Core ML](https://github.com/ggerganov/whisper.cpp#core-ml-support) +- Apple Silicon first-class citizen - optimized via ARM NEON, Accelerate framework, Metal and [Core ML](#core-ml-support) - AVX intrinsics support for x86 architectures - VSX intrinsics support for POWER architectures - Mixed F16 / F32 precision -- [4-bit and 5-bit integer quantization support](https://github.com/ggerganov/whisper.cpp#quantization) +- [4-bit and 5-bit integer quantization support](#quantization) - Zero memory allocations at runtime -- Vulkan support +- [Vulkan support](#vulkan-gpu-support) - Support for CPU-only inference -- [Efficient GPU support for NVIDIA](https://github.com/ggerganov/whisper.cpp#nvidia-gpu-support-via-cublas) -- [OpenVINO Support](https://github.com/ggerganov/whisper.cpp#openvino-support) -- [Ascend NPU Support](https://github.com/ggerganov/whisper.cpp#ascend-npu-support) +- [Efficient GPU support for NVIDIA](#nvidia-gpu-support) +- [OpenVINO Support](#openvino-support) +- [Ascend NPU Support](#ascend-npu-support) - [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/include/whisper.h) Supported platforms: @@ -89,7 +89,7 @@ Now build the [main](examples/main) example and transcribe an audio file like th ```bash # build the main example -make +make -j # transcribe an audio file ./main -f samples/jfk.wav @@ -100,7 +100,7 @@ make For a quick demo, simply run `make base.en`: ```text -$ make base.en +$ make -j base.en cc -I. -O3 -std=c11 -pthread -DGGML_USE_ACCELERATE -c ggml.c -o ggml.o c++ -I. -I./examples -O3 -std=c++11 -pthread -c whisper.cpp -o whisper.o @@ -224,7 +224,7 @@ ffmpeg -i input.mp3 -ar 16000 -ac 1 -c:a pcm_s16le output.wav If you want some extra audio samples to play with, simply run: ``` -make samples +make -j samples ``` This will download a few more audio files from Wikipedia and convert them to 16-bit WAV format via `ffmpeg`. @@ -232,18 +232,18 @@ This will download a few more audio files from Wikipedia and convert them to 16- You can download and run the other models as follows: ``` -make tiny.en -make tiny -make base.en -make base -make small.en -make small -make medium.en -make medium -make large-v1 -make large-v2 -make large-v3 -make large-v3-turbo +make -j tiny.en +make -j tiny +make -j base.en +make -j base +make -j small.en +make -j small +make -j medium.en +make -j medium +make -j large-v1 +make -j large-v2 +make -j large-v3 +make -j large-v3-turbo ``` ## Memory usage @@ -265,7 +265,7 @@ Here are the steps for creating and using a quantized model: ```bash # quantize a model with Q5_0 method -make quantize +make -j quantize ./quantize models/ggml-base.en.bin models/ggml-base.en-q5_0.bin q5_0 # run the examples as usual, specifying the quantized model file @@ -437,7 +437,7 @@ First, make sure your graphics card driver provides support for Vulkan API. Now build `whisper.cpp` with Vulkan support: ``` make clean -make GGML_VULKAN=1 +make GGML_VULKAN=1 -j ``` ## BLAS CPU support via OpenBLAS @@ -636,7 +636,7 @@ The [stream](examples/stream) tool samples the audio every half a second and run More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10). ```bash -make stream +make stream -j ./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000 ```