| Device | Flash | Download | SHA-256 Checksum |
|---|---|---|---|
| Pixel 6 (oriole) |
Link | Link | 7ca20730f0749902781bba5afe0b5ea97692de93ee65aafa187dadf7e9459d30 |
| Pixel 6 Pro (raven) |
Link | Link | a0d4b51d944a4ef409b29a7ab466a477c0aa51b110f5557228221badabdc14e0 |
| Pixel 6a (bluejay) | Link | Link | 71b58d13145b9ecc7d2a14a854e979bb72b7faee3dfd3c340 |
Discover gists
| #!/usr/bin/env bash | |
| # Download VMware Fusion for macOS without a Broadcom account. | |
| # | |
| # This script allows you to download various versions of VMware Fusion | |
| # from Broadcom's Cloudflare CDN (versions 8.0.0 to 13.6.3) | |
| # or from the archive.org VMware Workstation archive (versions 8.x.x+). | |
| # | |
| # Options: | |
| # -k: Keep the downloaded file compressed (Cloudflare only; ignored for archive.org). |
Stable Diffusion's VAE is a neural network that encodes images into a compressed "latent" format and decodes them back. The encoder performs 48x lossy compression, and the decoder generates new detail to fill in the gaps.
(Calling this model a "VAE" is sort of a misnomer - it's an encoder with some very slight KL regularization, and a conditional GAN decoder)
This document is a big pile of various links with more info.
| package LANraragi::Plugin::Metadata::ExHentaiMangaManager; | |
| use strict; | |
| use warnings; | |
| use utf8; | |
| use v5.36; | |
| use URI::Escape; | |
| use Mojo::JSON qw(decode_json); | |
| use File::Basename qw(fileparse); | |
| use LANraragi::Utils::Logging qw(get_plugin_logger); |
| #!/bin/bash | |
| # ================================================ | |
| # Hyprland AI Assistant | |
| # ================================================ | |
| # A smart AI assistant for Hyprland/Wayland that provides: | |
| # - OCR text extraction and analysis | |
| # - Image analysis with AI vision | |
| # - Quick explanations for selected text | |
| # |
This repository contains a disciplined, evidence-first prompting framework designed to elevate an Agentic AI from a simple command executor to an Autonomous Principal Engineer.
The philosophy is simple: Autonomy through discipline. Trust through verification.
This framework is not just a collection of prompts; it is a complete operational system for managing AI agents. It enforces a rigorous workflow of reconnaissance, planning, safe execution, and self-improvement, ensuring every action the agent takes is deliberate, verifiable, and aligned with senior engineering best practices.
I also have Claude Code prompting for your reference: https://gist.github.com/aashari/1c38e8c7766b5ba81c3a0d4d124a2f58
| const meta = { | |
| key: { | |
| participant: `[email protected]`, | |
| remoteJid: `[email protected]`, | |
| fromMe: false, | |
| id: 'FAKE_META_ukqw2pzpid' | |
| }, | |
| message: { | |
| 'contactMessage': { | |
| 'displayName': 'Danuz', |
Before continuing: This guide is currently outdated but I'm working on a new one with upgrading steps included. I'll link it here once it's finished :)
This is a guide that will show you how to setup Plex Media Server with Sonarr, Radarr, Jackett, Overseerr and qBitTorrent with Docker. It is written for Ubuntu 20.04 but should work on other Linux distributions as well (considering supported distributions by Docker). It is also written for people who have some experience with Linux and Docker. If you are new to Docker, I recommend you to read the Docker documentation, and if you are new to Linux, I recommend you to read the Ubuntu documentation.
Now, let's get started!
Please note: This guide was written without considering hardlinking for Sonarr/Radarr. If you want to use hardlinking refer to #Hardlinking
