EmotiVoice
Cgml
EmotiVoice | Cgml | |
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5 | 22 | |
6,369 | 39 | |
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8.9 | 8.6 | |
3 months ago | 4 months ago | |
Python | C++ | |
Apache License 2.0 | GNU Lesser General Public License v3.0 only |
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EmotiVoice
- FLaNK Stack Weekly 12 February 2024
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WhisperSpeech – An Open Source text-to-speech system built by inverting Whisper
Interested to see how it performs for Mandarin Chinese speech synthesis, especially with prosody and emotion. The highest quality open source model I've seen so far is EmotiVoice[0], which I've made a CLI wrapper around to generate audio for flashcards.[1] For EmotiVoice, you can apparently also clone your own voice with a GPU, but I have not tested this.[2]
[0] https://github.com/netease-youdao/EmotiVoice
[1] https://github.com/siraben/emotivoice-cli
[2] https://github.com/netease-youdao/EmotiVoice/wiki/Voice-Clon...
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Microsoft releases Windows AI studio to run and fine tune models locally
Interesting. I'll have to check to be sure, but I think maybe something is happening automagically if you have reasonably up to date nvidia drivers on the host OS, because I was able to run the EmotiVoice TTS docker (which requires nvidia gpu) from WSL2.
https://github.com/netease-youdao/EmotiVoice
- FLaNK Stack Weekly for 13 November 2023
- EmotiVoice: A Multi-Voice and Prompt-Controlled TTS Engine
Cgml
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Asynchronous Programming in C#
> Meant no offense
None taken.
> computervison project in c#
Yeah, for CV applications nuget.org is indeed not particularly great. Very few people are using C# for these things, people typically choose something else like Python and OpenCV.
BTW, same applies to ML libraries, most folks are using Python/Torch/CUDA stack. For that hobby project https://github.com/Const-me/Cgml/ I had to re-implement the entire tech stack in C#/C++/HLSL.
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Groq CEO: 'We No Longer Sell Hardware'
> If there is a future with this idea, its gotta be just shipping the LLM with game right?
That might be a nice application for this library of mine: https://github.com/Const-me/Cgml/
That’s an open source Mistral ML model implementation which runs on GPUs (all of them, not just nVidia), takes 4.5GB on disk, uses under 6GB of VRAM, and optimized for interactive single-user use case. Probably fast enough for that application.
You wouldn’t want in-game dialogues with the original model though. Game developers would need to finetune, retrain and/or do something else with these weights and/or my implementation.
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Ask HN: How to get started with local language models?
If you just want to run Mistral on Windows, you could try my port: https://github.com/Const-me/Cgml/tree/master/Mistral/Mistral...
The setup is relatively easy: install .NET runtime, download 4.5 GB model file from BitTorrent, unpack a small ZIP file and run the EXE.
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OpenAI postmortem – Unexpected responses from ChatGPT
Speaking about random sampling during inference, most ML models are doing it rather inefficiently.
Here’s a better way: https://github.com/Const-me/Cgml/blob/master/Readme.md#rando...
My HLSL is easily portable to CUDA, which has `__syncthreads` and `atomicInc` intrinsics.
- Nvidia's Chat with RTX is a promising AI chatbot that runs locally on your PC
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
I did a few times with Direct3D 11 compute shaders. Here’s an open-source example: https://github.com/Const-me/Cgml
Pretty sure Vulkan gonna work equally well, at the very least there’s an open source DXVK project which implements D3D11 on top of Vulkan.
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Brave Leo now uses Mixtral 8x7B as default
Here’s an example of a custom 4 bits/weight codec for ML weights:
https://github.com/Const-me/Cgml/blob/master/Readme.md#bcml1...
llama.cpp does it slightly differently but still, AFAIK their quantized data formats are conceptually similar to my codec.
- Efficient LLM inference solution on Intel GPU
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Vcc – The Vulkan Clang Compiler
> the API was high-friction due to the shader language, and the glue between shader and CPU
Direct3D 11 compute shaders share these things with Vulkan, yet D3D11 is relatively easy to use. For example, see that library which implements ML-targeted compute shaders for C# with minimal friction: https://github.com/Const-me/Cgml The backend implemented in C++ is rather simple, just binds resources and dispatches these shaders.
I think the main usability issue with Vulkan is API design. Vulkan was only designed with AAA game engines in mind. The developers of these game engines have borderline unlimited budgets, and their requirements are very different from ordinary folks who want to leverage GPU hardware.
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I made an app that runs Mistral 7B 0.2 LLM locally on iPhone Pros
Minor update https://github.com/Const-me/Cgml/releases/tag/1.1a Can’t edit that comment anymore, too late.
What are some alternatives?
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
PowerInfer - High-speed Large Language Model Serving on PCs with Consumer-grade GPUs
draw-a-ui - Draw a mockup and generate html for it
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
MockingBird - 🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time
mlx - MLX: An array framework for Apple silicon
lhotse - Tools for handling speech data in machine learning projects.
llamafile - Distribute and run LLMs with a single file.
voice100 - Voice100 includes neural TTS/ASR models. Inference of Voice100 is low cost as its models are tiny and only depend on CNN without autoregression.
clspv - Clspv is a compiler for OpenCL C to Vulkan compute shaders
clipea - 📎🟢 Like Clippy but for the CLI. A blazing fast AI helper for your command line
HIP - HIP: C++ Heterogeneous-Compute Interface for Portability