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vllm

A high-throughput and memory-efficient inference and serving engine for LLMs

Language:PythonApache-2.021685 197 3196

Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.

Language:PythonMIT20117 193 363

demucs

Code for the paper Hybrid Spectrogram and Waveform Source Separation

Language:PythonMIT7863 151 528

VALL-E-X

An open source implementation of Microsoft's VALL-E X zero-shot TTS model. Demo is available in https://plachtaa.github.io

Language:PythonMIT7396 83 148

hybridclr

HybridCLR是一个特性完整、零成本、高性能、低内存的Unity全平台原生c#热更新解决方案。 HybridCLR is a fully featured, zero-cost, high-performance, low-memory solution for Unity's all-platform native c# hotupdate.

Language:C++MIT6026 83 122

lmdeploy

LMDeploy is a toolkit for compressing, deploying, and serving LLMs.

Language:PythonApache-2.03084 29 958

bark-with-voice-clone

🔊 Text-prompted Generative Audio Model - With the ability to clone voices

Language:Jupyter NotebookNOASSERTION2935 47 77

DeepFilterNet

Noise supression using deep filtering

Language:PythonNOASSERTION2095 30 259

StableDiffusion-CheatSheet

A list of StableDiffusion styles and some notes for offline use. Pure HTML, CSS and a bit of JS.

Language:JavaScriptMIT1735 380

ParallelWaveGAN

Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN & HiFi-GAN & StyleMelGAN) with Pytorch

Language:Jupyter NotebookMIT1510 46 251

soundstorm-pytorch

Implementation of SoundStorm, Efficient Parallel Audio Generation from Google Deepmind, in Pytorch

Language:PythonMIT1142 51 15

Prompt-Free-Diffusion

Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models, arxiv 2023 / CVPR 2024

Language:PythonMIT713 12 25

vocos

Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis

Language:PythonMIT679 33 44

bark.cpp

Suno AI's Bark model in C/C++ for fast text-to-speech

Language:C++MIT618 34 74

bark-voice-cloning-HuBERT-quantizer

The code for the bark-voicecloning model. Training and inference.

Language:PythonMIT608 17 42

StyleDrop-PyTorch

Unoffical implement for [StyleDrop](https://arxiv.org/abs/2306.00983)

Language:PythonMIT552 9 25

Prompt-Diffusion

Official PyTorch implementation of the paper "In-Context Learning Unlocked for Diffusion Models"

Language:PythonApache-2.0362 7 13

AnimeInbet

Code and data for ICCV23 work "Deep Geometrized Cartoon Line Inbetweening"

Language:Python297 7 15

SoundStorm

The reproduced code for Google's SoundStorm

Language:Python231 20 26

Whispering-LLaMA

EMNLP 23 - Integrating Whisper Encoder to LLaMA Decoder for Generative ASR Error Correction

Language:Jupyter NotebookMIT204 4 10

aero

This repo contains the official PyTorch implementation of "Audio Super Resolution in the Spectral Domain" (ICASSP 2023)

Language:PythonMIT184 6 24

RAVE-Latent-Diffusion

Generate new latent codes for RAVE with Denoising Diffusion models.

Language:PythonMIT156 15 3

Barkify

Barkify: an unoffical training implementation of Bark TTS by suno-ai

Language:Python118 9 10

react-native-unity

React Native package to use Unity as library with RN app

Language:C#84 9 18

Kandinsky-2-textual-inversion

Kandinsky 2 — multilingual text2image latent diffusion model

Language:Jupyter NotebookApache-2.074 10

com.unity.addressables

Addressables extended with the ability to build multiple catalogs, ideal for traditional DLC purposes.

Language:C#NOASSERTION72 3 10

react-native-unity2

Embed Unity content in your React Native app!

Language:JavaMIT33 3 24

Philia-GUI

An easy to use imageboard scraper.

Language:TypeScript21 1 6

bark-with-voice-clone

🔊 Text-prompted Generative Audio Model - With the ability to clone voices

Language:Jupyter NotebookNOASSERTION19 10

com.unity.addressables

[Mirrored from UPM, without any changes. Maintained by Needle. Not affiliated with Unity Technologies.] 📦 The Addressable Asset System allows the developer to ask for an asset via its address. Once an asset (e.g. a prefab) is marked "addressable", it generates an address which can be called from anywhere. Wherever the asset resides (local or remote), the system will locate it and its dependencies, then return it.Use Window->Asset Management->Addressables to begin working with the system.Addressables use asynchronous loading to support loading from any location with any collection of dependencies. Whether you have been using direct references, traditional asset bundles, or Resource folders, addressables provide a simpler way to make your game more dynamic. Addressables simultaneously opens up the world of asset bundles while managing all the complexity.For usage samples, see github.com/Unity-Technologies/Addressables-Sample

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