HIP-CPU
whisper.cpp
HIP-CPU | whisper.cpp | |
---|---|---|
5 | 187 | |
104 | 31,174 | |
2.9% | - | |
7.2 | 9.8 | |
about 1 month ago | 7 days ago | |
C++ | C | |
MIT License | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
HIP-CPU
- HIP CPU
- [P] Pure C/C++ port of OpenAI's Whisper
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AMD publishes GPUFORT as Open Source to address CUDA’s dominance
If I'm reading this right, this is Fortran's equivalent of HIP, i.e. a way to (semi-)automatically convert CUDA-based solution to a more backend-independent one so that the same source can be run both on CUDA and ROCm GPUs (and potentially more; e.g. they also have an experimental CPU backend).
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Test Coverage with CUDA
So, I know that you asked about cuda, but this might actually be possible in hip, and you can convert your code to hip relatively easily. The path would be to use the CPU implementation (https://github.com/ROCm-Developer-Tools/HIP-CPU) and then run your code coverage on that.
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. It’s 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 – 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
🗣️🎙️ 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?
AdaptiveCpp - Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!
faster-whisper - Faster Whisper transcription with CTranslate2
libcudacxx - [ARCHIVED] The C++ Standard Library for your entire system. See https://github.com/NVIDIA/cccl
Whisper - High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model
rocFFT - Next generation FFT implementation for ROCm
bark - 🔊 Text-Prompted Generative Audio Model
HIP - HIP: C++ Heterogeneous-Compute Interface for Portability
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
stdgpu - stdgpu: Efficient STL-like Data Structures on the GPU
whisperX - WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
XNNPACK - High-efficiency floating-point neural network inference operators for mobile, server, and Web
llama.cpp - LLM inference in C/C++