Guardian88's Stars
public-apis/public-apis
A collective list of free APIs
satwikkansal/wtfpython
What the f*ck Python? 😱
Lightning-AI/pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
github/copilot-docs
Documentation for GitHub Copilot
fastai/fastbook
The fastai book, published as Jupyter Notebooks
openjdk/jdk
JDK main-line development https://openjdk.org/projects/jdk
github/docs
The open-source repo for docs.github.com
plasma-umass/scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
all-contributors/all-contributors
✨ Recognize all contributors, not just the ones who push code ✨
EmbarkStudios/rust-gpu
🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
github/training-kit
Open source courseware for Git and GitHub
ai-forever/ru-gpts
Russian GPT3 models.
tomer8007/widevine-l3-decryptor
A Chrome extension that demonstrates bypassing Widevine L3 DRM
vercel/micro-dev
The development environment for `micro`
all-contributors/app
🤖 A GitHub App to automate acknowledging contributors to your open source projects
all-contributors/cli
Tool to help automate adding contributor acknowledgements according to the all-contributors specification ✨
ethereum/staking-launchpad
The deposit launchpad for staking on Ethereum 🦏
codecov/example-node
Example repo for uploading reports to Codecov
behaviorbot/request-info
Requests more info from PRs/Issues with either the default title or a blank body
Canvasbird/canvasboard-backend
Canvasboard Backend built on NodeJS🚀
excellent-react/form
A Dead Simple and A Excellent React hook for React web application forms needs.
Guardian88/aika
Aika is a new type of artificial neural network designed to more closely mimic the behavior of a biological brain and to bridge the gap to classical AI. A key design decision in the Aika network is to conceptually separate the activations from their neurons, meaning that there are two separate graphs. One graph consisting of neurons and synapses representing the knowledge the network has already acquired and another graph consisting of activations and links describing the information the network was able to infer about a concrete input data set. There is a one-to-many relation between the neurons and the activations. For example, there might be a neuron representing a word or a specific meaning of a word, but there might be several activations of this neuron, each representing an occurrence of this word within the input data set. A consequence of this decision is that we have to give up on the idea of a fixed layered topology for the network, since the sequence in which the activations are fired depends on the input data set. Within the activation network, each activation is grounded within the input data set, even if there are several activations in between. This means links between activations serve two purposes. On the one hand, they are used to sum up the synapse weights and, on the other hand they propagate the identity to higher level activations.
Guardian88/all-contributors
✨ Recognize all contributors, not just the ones who push code ✨
Guardian88/copilot-docs
Documentation for GitHub Copilot
Guardian88/devdev606
Guardian88/docs
This is the open-source repo for docs.github.com.
Guardian88/oktoguard
Guardian Angel
Guardian88/orbot
The Github home of Orbot: Tor on Android (Also available on gitlab!)
Guardian88/pull
🤖 Keep your forks up-to-date via automated PRs
The-Blackguard-Family/transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.