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The simplest, fastest repository for training/finetuning medium-sized GPTs.
A curated list of awesome software for Apple's macOS.
FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI…
Official repository for our work on micro-budget training of large-scale diffusion models.
An open source deep research clone. AI Agent that reasons large amounts of web data extracted with Firecrawl
Magic to turn Cursor/Windsurf as 90% of Devin
A curated list for awesome discrete diffusion models resources.
Neural Networks: Zero to Hero
Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
Deep Reinforcement Learning: Zero to Hero!
LaTeX package and annotated examples for annotating equations using TikZ.
Mathematical finance cheat sheet.
🚀🧠💬 Supercharged Custom Instructions for ChatGPT (non-coding) and ChatGPT Advanced Data Analysis (coding).
[NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models
A code repository accompanying the paper "Transformers, parallel computation, and logarithmic depth" by Clayton Sanford, Daniel Hsu, and Matus Telgarsky.
Leaked GPTs Prompts Bypass the 25 message limit or to try out GPTs without a Plus subscription.
Examples of how to create colorful, annotated equations in Latex using Tikz.
Examples of matplotlib codes and plots
In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).
DevOps Guide - Development to Production all configurations with basic notes to debug efficiently.
A Python-embedded modeling language for convex optimization problems.
Find the right git commands without digging through the web.
A book-in-progress about the Linux kernel and its insides.
[CVPR 2020] Official Implementation: "Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models".