big_vision VS paperless-ngx

I think this is based off Google research https://github.com/google-research/big_vision

The the vision training models are available here: https://github.com/google-research/big_vision/tree/main which I am assuming, based on the research paper is what was used for the project.

Found relevant code at https://github.com/google-research/big_vision + all code implementations here

Official Github repository: https://github.com/google-research/big_vision

An open-source implementation of the Better plain ViT baselines for ImageNet-1k research paper in Google's JAX and Flax.

An update from some of the same authors of the original paper proposes simplifications to ViT that allows it to train faster and better.

Among these simplifications include 2d sinusoidal positional embedding, global average pooling (no CLS token), no dropout, batch sizes of 1024 rather than 4096, and use of RandAugment and MixUp augmentations. They also show that a simple linear at the end is not significantly worse than the original MLP head.

Simple ViT Research Paper: https://arxiv.org/abs/2205.01580

Official Github repository: https://github.com/google-research/big_vision

Developer updates can be found on: https://twitter.com/EnricoShippole

In collaboration with Dr. Phil 'Lucid' Wang: https://github.com/lucidrains

I steered a friend towards Paperless (and away from an LLM solution) as a way of searching/accessing GBs of architectural PDFs recently - so far, it’s apparently working well for them.

https://github.com/paperless-ngx/paperless-ngx

Paperless-ngx is a document management system that transforms your physical documents into a searchable online archive so you can find your physical documents easier. With features such as tags, full text search, multi-user permissions system, this is a dream for those who like to keep an organized folder of files and documents.

Since last year I’ve been configuring and maintaining my homelab setup and it is just amazing.

I’ve learned so much about containers, virtual machines and networking. Some of the self hosted applications like paperless-ngx [1] and immich [2] are much superior in terms of features than the proprietary cloud solutions.

With the addition of VPN services like tailscale [3] now I can access my homelab from anywhere in the world.

The only thing missing is to setup a low powered machine like NUC or any mini PC so I can offload the services I need 24/7 and save electricity costs.

If you can maintain it and have enough energy on weekends to perform routine maintenance and upgrades. I would 100% recommend setting up your own homelab.

[1] https://docs.paperless-ngx.com/

This has been posted a few times already, but I cannot tell you how life changing Paperless NGX is for organizing PDFs. As someone who wrangles all of the insurance and bills for my house, this open source software is so damn good.

https://docs.paperless-ngx.com/

I maintain Bash script to quickly set it up locally on Linux with Podman. Give it a spin if you want to kick the tires.

https://github.com/jdoss/ppngx

Personally, I use https://github.com/joeyates/imap-backup to archive all my emails and then only keep them on the remote server for as long as I need to (basically until I read them and respond or download an attachment into https://docs.paperless-ngx.com )