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@sinceohsix
sinceohsix / Installing LiveContainer+Sidestore.md
Last active March 22, 2026 20:16
Installing LiveContainer+SideStore from start to finish.

✴️ How to sideload with SideStore and LiveContainer

Last Edited: Dec 21, 2025 @ 6:34PM PST · Supports iOS versions 15.0 - 26.3 Beta

Make sure you are always using up-to-date guides to ensure full compatibility. The official SideStore documentation can be found here in case anything changes. For additional information and credits, scroll to the bottom of this page.


👋 Hello again, r/sideloaded!

This is version 2.0 of my iOS sideloading guide. By the end of this guide, you will be able to:

  • Sideload apps using SideStore
#!/bin/bash
set -euo pipefail
# Directory setup
APP_DIR="${HOME}/Applications"
ICON_DIR="${HOME}/.local/share/icons"
DESKTOP_DIR="${HOME}/.local/share/applications"
BIN_DIR="${HOME}/.local/bin"
# assume - https://granted.dev
export def --env --wrapped assume [...rest: string] {
const var_names = [
"AWS_ACCESS_KEY_ID",
"AWS_SECRET_ACCESS_KEY",
"AWS_SESSION_TOKEN",
"AWS_PROFILE",
"AWS_REGION",
"AWS_SESSION_EXPIRATION",
"GRANTED_SSO",
@clarkenheim
clarkenheim / Zip Codes to DMAs
Last active March 5, 2026 17:04
TSV file containing zip codes and the DMA they fall in to. Method: calculate the centre point of every zip code geo boundary, plot those points on a DMA boundary map, find the containing DMA of each zip centroid
This file has been truncated, but you can view the full file.
zip_code dma_code dma_description
01001 543 SPRINGFIELD - HOLYOKE
01002 543 SPRINGFIELD - HOLYOKE
01003 543 SPRINGFIELD - HOLYOKE
01004 543 SPRINGFIELD - HOLYOKE
01005 506 BOSTON (MANCHESTER)
01007 543 SPRINGFIELD - HOLYOKE
01008 543 SPRINGFIELD - HOLYOKE
01009 543 SPRINGFIELD - HOLYOKE
@baraldilorenzo
baraldilorenzo / readme.md
Last active September 13, 2025 12:17
VGG-16 pre-trained model for Keras

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman