bark.cpp
web_ffi
| bark.cpp | web_ffi | |
|---|---|---|
| 4 | 1 | |
| 579 | 19 | |
| - | - | |
| 8.1 | 0.0 | |
| 10 days ago | 6 months ago | |
| C++ | JavaScript | |
| MIT License | BSD 2-clause "Simplified" License |
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bark.cpp
- Show HN: I ported Suno AI's Bark model in C for fast realistic audio generation
- Bark.cpp: Port of Suno AI's Bark in C/C++ for fast inference
- I've open sourced my Flutter plugin to run on-device LLMs on any platform. TestFlight builds available now.
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Meta's Segment Anything written with C++ / GGML
Another GGML model port that I'm pretty excited about is https://github.com/PABannier/bark.cpp.
The Bark python model is very compute intensive and require a powerful GPU to get bearable inference speed. I really hope that bark.cpp with GPU/Metal support and quanticized model can bring useful inference speed on a laptop in the near future.
web_ffi
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I've open sourced my Flutter plugin to run on-device LLMs on any platform. TestFlight builds available now.
I leverage ffi and ffigen, but they don’t support web yet. I rely on them at the moment. But a quick search tells me there’s a decent chance to get this to work, there’s this package for example https://github.com/EP-u-NW/web_ffi (not maintained, but good nonetheless for inspiration).
What are some alternatives?
sam.cpp
stable-diffusion.cpp - Stable Diffusion in pure C/C++
Queryable - Run OpenAI's CLIP model on iOS to search photos.
vit.cpp - Inference Vision Transformer (ViT) in plain C/C++ with ggml
aub.ai - AubAI brings you on-device gen-AI capabilities, including offline text generation and more, directly within your app.
llm - An ecosystem of Rust libraries for working with large language models
StyleTTS2 - StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
whisper.cpp - Port of OpenAI's Whisper model in C/C++