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This repository guides developers wanting to contribute to the Scroll ecosystem. This repository guides developers wanting to contribute to Scroll. You can start contributing today, if you need ideas on getting started check out the issues tab. How to Contribute Thanks for your interest in contributing to Scroll. Check out the CONTRIBUTING page for a guide on how to contribute. Contributions Integrations Scroll has been integrated on the following projects: ethereum-lists/chains About Scro…
PyTorch code and models for V-JEPA self-supervised learning from video.
Minimal, clean, code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"Scalable Diffusion Models with Transformers (DiT)Official PyTorch Implementation Paper | Project Page | Run DiT-XL/2 This repo contains PyTorch model definitions, pre-trained weights and training/sampling code for our paper exploring diffusion models with transformers (DiTs). You can find more visualizations on our project page. Scalable Diffusion Models with Transformers William Peebles, Saining Xie UC Berkele…
Extensions for the Zed editorZed Extensions This is the central repository containing the extensions available for Zed. Authoring extensions See AUTHORING_EXTENSIONS.md for how to author your own extension and get it added to the extension registry. Looking for extension ideas? Check out: Theme requests
Build a REAL Software-as-a-Service app with AI features and payments & credits system that you might even turn into a side income or business idea using Next.js 14, Clerk, MongoDB, Cloudinary AI, and Stripe. An AI SaaS Platform Build this project step by step with our detailed tutorial on JavaScript Mastery YouTube. Join the JSM family! 📋 Table of Contents 🤖 Introduction ⚙️ Tech Stack 🔋 Features 🤸 Quick Start 🕸️ Snippets 🔗 …
An image processing pipeline for ROS.
Detect file content types with deep learningMagika Magika is a novel AI powered file type detection tool that rely on the recent advance of deep learning to provide accurate detection. Under the hood, Magika employs a custom, highly optimized Keras model that only weighs about 1MB, and enables precise file identification within milliseconds, even when running on a single CPU. In an evaluation with over 1M files and over 100 content types (covering both binary and textual file formats), Magika a…