Building your own Stable Diffusion model to make your own NFT collection.
If you look at the link here you will see a NFT collection in a NFT marketplace
It is an NFT collection built with Ai Art sitting on an Ethereum layer 2 testnet, but there is a twist. Read on to see how I made it.
I generated 100 or so of the Bauhaus dogs from the list of the top 200 AKC dog by using InvokeAI's ability to automate by putting the same art prompts in a text file with just the breed as difference in the prompt.
Example Prompt:
portrait of a dog, Bulldog, bauhaus, red background, black and red colors, adobe illustrator, vector art
Once generated, I took about 40 of the best images and trained up my own Stable Diffusion model. I used the following Dreambooth Google Colab:
After the model generation was complete I ran the prompt.txt list back through InvokeAI with my custom model loaded up. It generated the 100 images you see in the NFT collection.
I then used some scripting and internet magic to upload the metadata and images to IPFS. I used the Breed, seed, sampler, steps, and cfg to fill out the metadata for each NFT. Once uploaded, I used the ThirdWeb.io to fire up an ERC721 contract on Optimism in the Goerli Optimism testnet. I like using the ThirdWeb's dashboard UI as it makes releasing simple NFT contract easy.
Finally, once all that was done I minted out the 100 NFTs so they'd show up. On the L2 testnet the transactions are super cheap.
So, I used AI art to generate a model to generate more AI art and then put that on a layer 2 on Ethereum.
Pretty neat eh?
For more info on how to train your own Stable Diffusion model I wrote up a post here:
Jeremy
If you have any questions or comments, please feel free to reach out to me on social networks.
Jeremy
