Hi again! This is a update to my previous post [MageTrail V0.25](https://www.reddit.com/r/StableDiffusion/s/q8qYHd4YIY) where I continued this tech demo toy model thingy called

***MageTrail***, a Danbooru/E621 proof of concept Full-Finetune of Microsoft's MageFlow 4B T2I model, using a diversity maximized condensed 41k images dataset (originally made by Lodestone, the creator of the Chroma model lineage) as a way to tune booru concept and tags based prompting + Illustration capabilities into the model without having to tune with the full booru dataset. (Potentially costing 20k-50k+ dollars). [Civitai](https://civitai.red/models/2918004/magetrail-28b-danboorue621-finetune-based-on-mageflow) [HuggingFace](https://huggingface.co/RicemanT/MageTrail)

This update is a major one, the biggest update yet when it comes to actual training. V0.1 to V0.3 have spent 593 dollars in total (425 H100 HBM3 hours) and has ultimately shown the model potential in quickly learning and adapting booru concept and tags to its knowledge base, which is the initial scope of my two Banodoco grant request, but after training and testing the model has clearly outgrown its limited 41k dataset in my opinion (which was expected), with model stability improvement unfortunately slowing to a crawl and the model mainly improve massively through learning of a lot of new concepts.

**Positive**

* Model learned a lot of concepts and is generally somewhat more stable in some area
* Pretty much have learn everything that it can learn with the limited dataset
* Recent research discovery reveal that with some code changes, the model can be completely trained like normal with Flux2VAE  (the current best VAE that is available for open source) without needing realignment training which would have costed so much money for any other model. This mean for future releases this model will be a full Flux2VAE arch and inherit all of the advantages the VAE offers (best details, best reconstruction, best texture rendering out of all open VAE, making the model learn concept/details/texture faster and better, which is a great boon for styles).
* [https://huggingface.co/Muinez/mage-flow-ft](https://huggingface.co/Muinez/mage-flow-ft) , a now abandoned test project by Muinez, based on V0.2 2.8B arch of my model, was trained with 500h of L40S (200-300 dollars), and while extremely undertrained, shows that if trained with full 10mil+ dataset, the model can learn all characters and style, all but confirming MageFlow potential as a great contender for foundational training on 1B-4B scale.

**Negative**

* Model hasn't stabilized as fast as I've hoped, and now i've learned that you practically need minimum 1mil+ image to train in for model to generalize well and be stable enough as a "base" for other people to tune on (Just like old lineage like Animagine, KohakuXL, Illustrious, NoobAI), and that the booru essence method is unfortunately not a full shortcut to that.... I'm still very green to large scale model finetuning 😥
* The problem all model trainers without major VC's/sponsor backing faces, I've about ran out of money now.

So what's the plan? Since I've decided that this will be the last release where I'll be using Lodestone's Rock booru essence dataset, for the next few weeks to month I'll be taking a break and focusing on start of uni semester (yknow irl stuffs I can't be a full AI degen past summer). Furthermore the time will also be used for me to curate and prepare a 10k+ artist style collection dataset (200000+ images), comprised of danbooru/gelbooru/e621 artists and other outlier sources.

So, TLDR for the future ->

***BIG GOAL***: **Due to** [**https://huggingface.co/Muinez/mage-flow-ft**](https://huggingface.co/Muinez/mage-flow-ft) **, I now completely believe in MageFlow being the next best small scale arch to replace Anima in the Illustration sphrere, the model has shown to have the ability to learn concepts/characters/styles efficiently while being a superior architecture to most contemporary. I pledge to finetune a Anima successor if given 25k-100k dollars of funding from the open source community/any generous patrons.**

***SMALL GOAL***: **Gather funding of 1000-2000\~ dollars to finetune 10k-100k artist styles into the model (200k-3 million images finetune, planned V0.4-V1) and help further with convergence/aesthetic improvement if the aforementioned big goal above hasn't been reached.** Artist tuning will proceed anyway as a hobbyist project even if I don't receive any donation, once I regain access to x4 A4000, but training on that will be months slower than being able to blast it with at least x1 H100, so yes any donations at all will help towards the project being in a "usable" state faster instead of just being a interesting but unstable toy model.

**Any donation will help with achieving this goal, you can do so through:**

***Crypto (Prefered, cause Kofi/Paypal money transfer time is ass and they take a big cut)***

**0x6a4bc748cd0bb9ced9a360eb0eb79f4f106614f8 (USDT - BEP20 Network)**

**12PPVYUeS1MerNp38Tpns5qXR6cmhu9tws (Bitcoin - BTC Network)**

**0x6a4bc748cd0bb9ced9a360eb0eb79f4f106614f8 (Ethereum - ERC20 Network)**

**FitfJAsxLUBuSgDJJaHgBXJpt1sMm5FzF1Tvf1SHW5Up (Solana - SOL network)**

Please handle your money carefully and make sure the address you're sending to is correct.

***Ko-fi***

[**https://ko-fi.com/talanartvn**](https://ko-fi.com/talanartvn)

**If you want to make a donation and make sure it goes through to me and the money is not lost, please contact me through Discord (user:** talannnn) **so that we can arrange sending small test amount (for crypto) to make sure the money goes through.**

# Acknowledgments

Beeg thanks to:

* [Banodoco](https://www.banodoco.ai/) and [their Discord](https://discord.gg/yzwcNaSEz) — Their 88.77 dollar initial grant and further support on future requests made this project possible, the biggest thanks to them
* [Lodestone Rock](https://huggingface.co/lodestones) — Creator of the original version of the booru essence dataset that this model is trained on
* [Motimalu](https://civitai.red/user/motimalu) — Inspiration behind finetuning practices and configs
* [Bluvoll](https://github.com/bluvoll/diffusion-pipe) — Creator of the modified 2.8B arch, diffusion-pipe fork derived from to use for training, and general training advice
* [Anzhc](https://huggingface.co/Anzhc) — general training advice
* [Nruaif](https://huggingface.co/Shio-Koube) — diffusion-pipe fork derived from to use for training, and general dataset handling/training advice
* [Astromahdi](https://gpu.garden/) — jupyter workspace and storage where I processed and store the dataset
* [Heato-Red](https://www.reddit.com/user/heato-red/) — Designer of model page logo
* [animetimm/DeepGHS](https://huggingface.co/animetimm/convnextv2_huge.dbv4-full) — Danbooru tagging model
* [RedRocket](https://huggingface.co/RedRocket/Hydra) — E621 tagging model
* Format inspired by [Motimalu's Kirazuri diary](https://github.com/motimalu/diffusion-training-configs/blob/main/diffusion-pipe/anima/notes/kirazuri4.0-notes%20.md)

MageTrail - V0.3 Update: Modified MageFlow 2.8B Danbooru/E621 Finetune has reach initial scope