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Fantasy Card Diffusion (MTG)

21
223
0
10
Verified:
SafeTensor
Type
Checkpoint Trained
Stats
223
0
Reviews
Published
May 22, 2024
Base Model
SD 1.5
Trigger Words
mtg card art
Hash
AutoV2
AEC66A60FA
default creator card background decoration
volrath50's Avatar
volrath50

This is a safetensors version of a model I trained back in November 2022, likely the first publically available general purpose MTG art model. Surprisingly, I'm not sure if a better general MTG art model has actually been released since November 2022.

I trained this in the early days of Stable Diffusion, before Civitai was really a thing, to my knowledge. I posted a lot of information and a lot of good examples on my Huggingface page for it: volrath50/fantasy-card-diffusion · Hugging Face.

The name, fantasy-card-diffusion, was deliberately vague and doesn't use "MTG" or "Magic", because like a week before I posted the model on Huggingface, WotC shut down some guy's custom card creator, and I figured it was better to go super-generic with the name.

Because I trained it in November 2022, it only "knows" MTG after that point. Sadly, perhaps, I don't think I've actually managed to play MTG since about then , so I don't really know MTG after that point, either. :(

As noted, lots of information and examples on Huggingface, but I'll quote some of the key points:

A comprehensive fine-tuned Stable Diffusion model for generating fantasy trading card style art, trained on all currently available Magic: the Gathering card art (~35k unique pieces of art) to 140,000 steps, using Stable Diffusion v1.5 as a base model. Trained on thousands of concepts, using tags from card data. Has a strong understanding of MTG Artists, planes, sets, colors, card types, creature types and much more.

Prompts: For best results, prompt the model with card information, like you were writing out a custom MtG card, with the phrase "MTG card art" and an art description

Example: "MTG card art, Fiery Merfolk, by Chris Rahn, 2021, creature - merfolk wizard, blue, red, ur, izzet, ravnica, gtp, rtr, grn, an izzet league merfolk, swimming in a ravnica river, casting a fire spell, flames, water, contrast, beautiful composition, intricate details"

Using the Model

The model was trained on MtG card information, not art descriptions. This has the effect of preserving most non-MtG learning intact, allowing you to mix MtG card terms with an art description for great customization.

Each card was trained with card information pulled from Scryfall in the following format:

MTG card art, [Card Name], by [Artist], [year], [colors (words)], [colors (letters)], [card type], [rarity], [set name], [set code], [plane], [set type], [watermark], [mana cost], [security stamp], [power/toughness], [keywords], [promo type], [story spotlight]

A few examples of actual card data in this format:

MTG card art, Ayula, Queen Among Bears, by Jesper Ejsing, 2019, Green, G, Legendary Creature - Bear, rare, Modern Horizons, mh1, draft_innovation, 1G, None, 2/2, Fight,

MTG card art, Force of Will, by Terese Nielsen, 1996, Blue, U, Instant, uncommon, Alliances, all, Dominaria, Terisiare, Ice Age, expansion, 3UU,