XNNPACK
whisper.cpp
XNNPACK | whisper.cpp | |
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8 | 187 | |
1,700 | 31,174 | |
1.6% | - | |
9.9 | 9.8 | |
6 days ago | 8 days ago | |
C | C | |
GNU General Public License v3.0 or later | MIT License |
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XNNPACK
- Xnnpack: High-efficiency floating-point neural network inference operators
- Can a NPU be used for vectors?
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Performance critical ML: How viable is Rust as an alternative to C++
Why are you writing your own inference code in C++ or Rust instead of using some kind of established framework like XNNPACK?
- [P] Pure C/C++ port of OpenAI's Whisper
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[Discussion] Is XNNPACK a part of mediapipe? or should be additionally configured with mediapipe?
XNNPACK - https://github.com/google/XNNPACK
- WebAssembly Techniques to Speed Up Matrix Multiplication by 120x
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Prediction: Macs won't see many new games, no matter how powerful their hardware is
Ok, concrete example time! At work, we're going to be using some software which includes XNNPACK, which is a library of highly-optimised operations for doing neural-network inference. This is the sort of thing where people have gone in and specifically tuned for performance, and nope, there's no attempt at all made to have code which is different for Intel/AMD or Apple/Other ARM. What they target is elements of the ISA, like NEON (i.e. ARM SIMD) and SSE, AVX etc. on x86(-64). And Wasm SIMD for Wasm.
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Where are Nvidia's DLSS models stored and how big are they?
It's quite simple. https://github.com/google/XNNPACK for example.
whisper.cpp
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Show HN: I created automatic subtitling app to boost short videos
whisper.cpp [1] has a karaoke example that uses ffmpeg's drawtext filter to display rudimentary karaoke-like captions. It also supports diarisation. Perhaps it could be a starting point to create a better script that does what you need.
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1: https://github.com/ggerganov/whisper.cpp/blob/master/README....
- LLaMA Now Goes Faster on CPUs
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LLMs on your local Computer (Part 1)
The ggml library is one of the first library for local LLM interference. Itβs a pure C library that converts models to run on several devices, including desktops, laptops, and even mobile device - and therefore, it can also be considered as a tinkering tool, trying new optimizations, that will then be incorporated into other downstream projects. This tool is at the heart of several other projects, powering LLM interference on desktop or even mobile phones. Subprojects for running specific LLMs or LLM families exists, such as whisper.cpp.
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Voxos.ai β An Open-Source Desktop Voice Assistant
I'm not sure if it is _fully_ openai compatible, but whispercpp has a server bundled that says it is "OAI-like": https://github.com/ggerganov/whisper.cpp/tree/master/example...
I don't have any direct experience with it... I've only played around with whisper locally, using scripts.
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Jarvis: A Voice Virtual Assistant in Python (OpenAI, ElevenLabs, Deepgram)
unless i'm misunderstanding `whisper.cpp` seems to support streaming & the repository includes a native example[0] and a WASM example[1] with a demo site[2].
[0]: https://github.com/ggerganov/whisper.cpp/tree/master/example...
- Wchess
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I've open sourced my Flutter plugin to run on-device LLMs on any platform. TestFlight builds available now.
Usage 1: Good to transcribe audio. An example use case could be to summarize YouTube videos or long courses. Usage 2: You talk with voice to your AI that responds with text (later with audio too). - https://github.com/ggerganov/whisper.cpp
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Scrybble is the ReMarkable highlights to Obsidian exporter I have been looking for
π£οΈποΈ whisper.cpp (offline speech-to-text transcription, models trained by OpenAI, CLI based, browser based)
- Whisper.wasm
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Whisper C++ not working for me. Anyone else?
Has anyone played around with Whisper C++ for swift? I'm hitting a snag even on the demo. I've downloaded the github repo and everything matches up with this video [ https://youtu.be/b10OHCDHDQ4 ] but when he hits the transcribe button, it actually prints out the captioning. When I do it, it skips that part and just says "Done...". But it, does everything else - plays the audio, says it's transcribing.. just doesn't show me the transcription: and it's not in the debug window either. But the demo isn't throwing any errors, and I haven't messed with the code really so this is their example. https://github.com/ggerganov/whisper.cpp
What are some alternatives?
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
faster-whisper - Faster Whisper transcription with CTranslate2
gemm-benchmark - Simple [sd]gemm benchmark, similar to ACES dgemm
Whisper - High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model
cpuid2cpuflags - Tool to generate CPU_FLAGS_* for your CPU
bark - π Text-Prompted Generative Audio Model
wasmblr - C++ WebAssembly assembler in a single header file
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
Genann - simple neural network library in ANSI C
whisperX - WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
ruby-fann - Ruby library for interfacing with FANN (Fast Artificial Neural Network)
llama.cpp - LLM inference in C/C++