antond

graphcast

lightningcss

An extremely fast CSS parser, transformer, bundler, and minifier written in Rust.

perfect-shape

Perfect Shape is a collection of geometric algorithms that are mostly useful for GUI manipulation like checking containment of a point in popular geometric shapes such as rectangle, square, arc, circle, polygon, and paths containing lines, quadratic bézier curves, and cubic bezier curves. Also, some general math algorithms like IEEE-754 Remainder.

jest-preview

Debug your Jest tests. Effortlessly.🛠🖼

astro

The web framework for content-driven websites. ⭐️ Star to support our work!

kuna

Kuna Smart Home Security Custom Integration for Home Assistant

pywemo

Python module to discover and control WeMo devices.

esbuild

An extremely fast bundler for the web

ssl-tools

Ruby tools to help with debugging certificates for SSL connections

sorbet

A fast, powerful type checker designed for Ruby

steep

Static type checker for Ruby

ActiveRecordExtended

Adds additional postgres functionality to an ActiveRecord / Rails application

vite

Next generation frontend tooling. It's fast!

Audio-Super-Resolution

Enhancment of Audio Quality (Bit-Depth and Sampling-Rate) using Deep Learning.

audio-super-res

Audio super resolution using neural networks

deep-audio-super-resolution

Deep neural network for audio super-resolution tasks

gcc-nmf

Real-time GCC-NMF Blind Speech Separation and Enhancement

Speech-enhancement

Deep learning for audio denoising

Awesome-Speech-Enhancement

A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.

sednn

deep learning based speech enhancement using keras or pytorch, make it easy to use

DeepXi

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.

segan

Speech Enhancement Generative Adversarial Network in TensorFlow

denoiser

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

gpt-neo

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

gpt-neox

An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries

tokenizers

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

awesome-gpt3

audio-cleaning-deep-learning

Deep Learning model that cleans audio of empty audio, miscellaneous sounds, etc. Suitable for podcast editing.

the-art-of-command-line

Master the command line, in one page