A feature rich Emacs (kickstarter) config for (neo)vi(m)mers Requirements · Installation · Available Commands · Contributing --- Welcome to Emacs-Kick, a feature-rich Emacs configuration designed for users familiar with Vim, Neovim, and Vi. With this setup, you don't need to leave behind your favorite terminal or tools like yazi, starship, lazygit, and lazydocker just to give Emacs a try.
That being said, some enhancements added compared to the original repo: :heavycheckmark: Possible to train in other languages :heavycheckmark: Hifigan added, allowing for faster inference at the cost of quality. :heavycheckmark: whisper-v3 added as a chooseable option for whisperx :heavycheckmark: Output conversion using RVC This is a fork of the repo originally located here: https://git.ecker.tech/mrq/ai-voice-cloning.
By Daniel Demmler, Thomas Schneider and Michael Zohner (ENCRYPTO, TU Darmstadt) in Network and Distributed System Security Symposium (NDSS'15). --- ABY efficiently combines secure computation schemes based on Arithmetic sharing, Boolean sharing, and Yao’s garbled circuits and makes available best-practice solutions in secure two-party computation.
Core Rust hash-signature workspace with: To build the library: For release build: To build the Solana program: The crate exposes SHRINCS verifier, signer, and account bindings under src/wasm/ behind the wasm-bindings feature. The supported build path is bin/build-wasm.sh, which runs cargo build for wasm32-unknown-unknown and then the wasm-bindgen CLI (not wasm-pack) for the nodejs and web targets.
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets. We are happy to receive feedback and contributions.
If you are a musician looking to use Surge XT, please download the appropriate binary from our website. Surge Synth Team makes regular releases for all supported platforms.
Naive linter for English prose for developers who can't write good and wanna learn to do other stuff good too. Important: Do not use this tool to be a jerk to other people about their writing.
Through my travels I've discovered it's possible to write a fully functional Terminal User Interface in BASH. The object of this guide is to document and teach the concepts in a simple way.
Training and inference code for audio generation models Requires PyTorch 2.5 or later for Flash Attention and Flex Attention support. Development for the repo is done in Python 3.10.
code examples with explanations, different use cases and links to further readings. It is a playground because you may change or add the code to see how it works and test it out using assertions.