update - 4th Feb 2023: V15 version added
update - 19th Jan 2023: Johnson has been experimenting and passed this to me to include on this listing:
djzGingerTomCatV21-512-inpainting
please use an SD-V21-512-inpainting.yaml config (included below)
we recommend using latent nothing mask mode.
This Model combines two GingerTomCat datasets, created by DriftJohnson. It is then reinforced by two textual inversions;
the KittyPics embedding by stille_willem &
the Point-E negative embedding by Doctor_Diffusion
3x3 grid used both embeddings, 2x2 grid shows same seed outputs with some suggested upscaler settings.
showcase credit: DriftJohnson
"strong style" Models are intended to be merged with each other and any model for Stable Diffusion 2.1 -- although you can also use these without the Trigger word like any model
I recommend merging with 0.5 (50/50 blend) then using prompt weighting to control the Aesthetic gradient.
example merged model prompt with automatic1111:
(GingerTomCat:1.2) (yourmodeltoken:0.8)
if you drop the "djz" and the "V21" what remains is the token you need to call up the concept in the model. All examples shown were the Raw Token, no other words. Tokens are case sensitive and in almost all models it will match the filename.
It is possible to merge these models with each other using a different value. It is possible to pair models and then merge those resulting models. In this way we can blend abstract concepts together and then weight the tokens to achieve the result we may wish to create.
Of course to eliminate all those tokens, you can simply train a new custom model from the outputs, which means you are back to a single token.
A video explanation will follow, but for now the above explanation should do. We are focused on getting as many style/aesthetic models into artist hands to enhance the creativity already at their finger tips.
Art Freedom for all!!
[all original artwork used for training with full permission from Drift Johnson]
djz GingerTomCat V21-768 / V21-512-inpainting / V15 is a highly specialized Image generation AI Model of type Safetensors / Checkpoint AI Model created by AI community user driftjohnson. Derived from the powerful Stable Diffusion (SD 1.5) model, djz GingerTomCat V21-768 / V21-512-inpainting / V15 has undergone an extensive fine-tuning process, leveraging the power of a dataset consisting of images generated by other AI models or user-contributed data. This fine-tuning process ensures that djz GingerTomCat V21-768 / V21-512-inpainting / V15 is capable of generating images that are highly relevant to the specific use-cases it was designed for, such as cats, ginger, tom.
With a rating of 5 and over 1 ratings, djz GingerTomCat V21-768 / V21-512-inpainting / V15 is a popular choice among users for generating high-quality images from text prompts.
Yes! You can download the latest version of djz GingerTomCat V21-768 / V21-512-inpainting / V15 from here.
To use djz GingerTomCat V21-768 / V21-512-inpainting / V15, download the model checkpoint file and set up an UI for running Stable Diffusion models (for example, AUTOMATIC1111). Then, provide the model with a detailed text prompt to generate an image. Experiment with different prompts and settings to achieve the desired results. If this sounds a bit complicated, check out our initial guide to Stable Diffusion – it might be of help. And if you really want to dive deep into AI image generation and understand how set up AUTOMATIC1111 to use Safetensors / Checkpoint AI Models like djz GingerTomCat V21-768 / V21-512-inpainting / V15, check out our crash course in AI image generation.