coral-pi-rest-server
whisper.cpp
coral-pi-rest-server | whisper.cpp | |
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44 | 187 | |
66 | 31,649 | |
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0.0 | 9.8 | |
7 months ago | 3 days ago | |
Jupyter Notebook | C | |
MIT License | MIT License |
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coral-pi-rest-server
- BeagleY-AI: 4 TOPS-capable $70 board from Beagleboard
- Do you recommend Orange PI for ML or LLM projects?
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Framework for machine learning?
That said, you can always look at something like https://coral.ai/products/accelerator/ to help with the performance you need.
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Mini PC for AI
Should only be ~$60 https://coral.ai/products/accelerator/
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What are some USB devices worth using in a Home Lab Environment?
The Coral USB accelerator might be of interest if you want to do some light ML with a low power budget.
- Is a PCIe x1 enough for light ML tasks
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Would I be able to run ggml models such as whisper.cpp or llama.cpp on a raspberry pi with a coral ai USB Accelerator?
However, a pi doesn't have the strength to run something like Llama.cpp, of course, so I've been considering using something like the Coral USB Accelerator (https://coral.ai/products/accelerator). As I've been learning more about it, it seems to be very geared towards TensorFlow Lite models. But whisper.cpp and Llama.cpp use ggml models.
- Looking for a Mini PC for Home Assistant and Frigate.
- AI development suite on a stick?
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Modder wires ChatGPT into Skyrim VR so NPCs can roleplay and remember past conversations
Recently found this thing, though I haven't found a use case for me.
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?
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
faster-whisper - Faster Whisper transcription with CTranslate2
double-take - Unified UI and API for processing and training images for facial recognition.
bark - π Text-Prompted Generative Audio Model
rpi-urban-mobility-tracker - The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.
Whisper - High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model
opentts - Open Text to Speech Server
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
HASS-coral-rest-api - Coral REST API for HASS
whisperX - WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
os-nvr
llama.cpp - LLM inference in C/C++