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readme : update links and make commands (#2489)

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* Update links to headers in README.md

* Add link to Vulkan section in README.md

* Add "-j" for parallelism for "make" in README.md

* Update README.md
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@ -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: High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model:
- Plain C/C++ implementation without dependencies - 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 - AVX intrinsics support for x86 architectures
- VSX intrinsics support for POWER architectures - VSX intrinsics support for POWER architectures
- Mixed F16 / F32 precision - 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 - Zero memory allocations at runtime
- Vulkan support - [Vulkan support](#vulkan-gpu-support)
- Support for CPU-only inference - Support for CPU-only inference
- [Efficient GPU support for NVIDIA](https://github.com/ggerganov/whisper.cpp#nvidia-gpu-support-via-cublas) - [Efficient GPU support for NVIDIA](#nvidia-gpu-support)
- [OpenVINO Support](https://github.com/ggerganov/whisper.cpp#openvino-support) - [OpenVINO Support](#openvino-support)
- [Ascend NPU Support](https://github.com/ggerganov/whisper.cpp#ascend-npu-support) - [Ascend NPU Support](#ascend-npu-support)
- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/include/whisper.h) - [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/include/whisper.h)
Supported platforms: Supported platforms:
@ -89,7 +89,7 @@ Now build the [main](examples/main) example and transcribe an audio file like th
```bash ```bash
# build the main example # build the main example
make make -j
# transcribe an audio file # transcribe an audio file
./main -f samples/jfk.wav ./main -f samples/jfk.wav
@ -100,7 +100,7 @@ make
For a quick demo, simply run `make base.en`: For a quick demo, simply run `make base.en`:
```text ```text
$ make base.en $ make -j base.en
cc -I. -O3 -std=c11 -pthread -DGGML_USE_ACCELERATE -c ggml.c -o ggml.o 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 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: 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`. 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: You can download and run the other models as follows:
``` ```
make tiny.en make -j tiny.en
make tiny make -j tiny
make base.en make -j base.en
make base make -j base
make small.en make -j small.en
make small make -j small
make medium.en make -j medium.en
make medium make -j medium
make large-v1 make -j large-v1
make large-v2 make -j large-v2
make large-v3 make -j large-v3
make large-v3-turbo make -j large-v3-turbo
``` ```
## Memory usage ## Memory usage
@ -265,7 +265,7 @@ Here are the steps for creating and using a quantized model:
```bash ```bash
# quantize a model with Q5_0 method # 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 ./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 # 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: Now build `whisper.cpp` with Vulkan support:
``` ```
make clean make clean
make GGML_VULKAN=1 make GGML_VULKAN=1 -j
``` ```
## BLAS CPU support via OpenBLAS ## 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). More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10).
```bash ```bash
make stream make stream -j
./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000 ./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
``` ```