gmchad

grok-1

Grok open release

zed

Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.

llm.c

LLM training in simple, raw C/CUDA

tree-sitter

An incremental parsing system for programming tools

mlx

MLX: An array framework for Apple silicon

blog_os

Writing an OS in Rust

SWE-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.47% of bugs in the SWE-bench evaluation set and takes just 1 minute to run.

mamba

Mamba SSM architecture

minbpe

Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.

ZLUDA

CUDA on ??? GPUs

chatgpt_system_prompt

A collection of GPT system prompts and various prompt injection/leaking knowledge.

VoiceCraft

Zero-Shot Speech Editing and Text-to-Speech in the Wild

GPU-Puzzles

Solve puzzles. Learn CUDA.

skyvern

Automate browser-based workflows with LLMs and Computer Vision

cannon.js

A lightweight 3D physics engine written in JavaScript.

self-instruct

Aligning pretrained language models with instruction data generated by themselves.

egjs-infinitegrid

A module used to arrange card elements including content infinitely on a grid layout.

SWE-bench

[ICLR 2024] SWE-Bench: Can Language Models Resolve Real-world Github Issues?

S-LoRA

S-LoRA: Serving Thousands of Concurrent LoRA Adapters

notesGPT

Record voice notes & transcribe, summarize, and get tasks

priompt

Prompt design using JSX.

Sketchbook

3D playground built on three.js and cannon.js.

tokencost

Easy token price estimates for 400+ LLMs. TokenOps.

anthropic-sdk-python

pyvene

Stanford NLP Python Library for Understanding and Improving PyTorch Models via Interventions

funding-simulator

Startup Funding Simulator

gpt-analyst

GPT-Analyst: A GPT for GPT analysis and reverse engineering

hype

A feed of trending repos/models from GitHub, Replicate, HuggingFace, and Reddit.

ConceptARC-Representations

This repository explains and provides examples for "concept anchoring" in GPT4.

oss-checklist

In order to create a healthy, rich community full of globally diverse contributors, we must make it easy for everyone to use the project, clearly explain how to contribute, build personal relationships, make people feel included, and create a safe environment by setting a code of conduct.