SciStyle
v1 of SciStyle is a test model for a new image captioning pipeline I've been working on. The model was trained on a subset of 1k images of various styles/mediums. Surprised by the results for a model trained on only 1k images, I decided to release it here. The full model is currently being worked on.
For more info on the image captioning pipeline, refer to my Discord thread linked bellow
Questions/Feedback/Updates?
Visit my thread on the Unstable Diffusion Discord
Info
S&D
Base Model: Stable Diffusion v1.5
Type: Experimental Fine-tune
Clip: 1
Medium: Multi-medium
Caption Style: Natural Language + Booru Style
Dataset Size: Subset, 4k images out of 25k images + DnD dataset
Training Resolution: 768x768
Difference from v1: More fantasy focused, additional training on a DnD dataset.
V1
Base Model: Stable Diffusion v1.5
Type: Experimental Fine-tune
Clip: 1
Medium: Multi-medium
Caption Style: Natural Language + Booru Style
Dataset Size: Subset, 1k images out of 25k images
Training Resolution: 768x768
V2
Base Model: Stable Diffusion v1.5
Type: Experimental Fine-tune
Clip: 1
Medium: Multi-medium
Caption Style: Natural Language + Booru Style
Dataset Size: Subset, 6.5k images out of 25k images
Training Resolution: 768x768
Difference from v1: More species from various Sci-fi and fantasy universes.
Features
Multi-medium: Capable of generating images from multiple art mediums, simply include the medium in the prompt.
Natural Language & Booru: Accepts both natural language prompts and booru style prompts.
Extra Detail: Understands subtle details often skipped by SD models. Such as, number of objects/subjects in a scene, background information, color information for various parts of the image, atmosphere, ect.. (see my discord thread above for more info on how this is achieved.)
Flexible: Can easily be merged with other SD1.5 checkpoints / LoRAs
Usage
Special Tokens:
SciStyle, can be used as a class token at the beginning of the prompt, but is not necessary.Tag for various art mediums, i.e.,
a comic book illustration of,90s anime screencap ofor, simply add the medium towards the end of the prompt;comic book illustration,photorealistic. These are just examples of tag placement. Feel free to experiment with other mediums
Recommended Settings
Sampler/Solver:
Euler a
Steps: 20 - 32
CFG: 6 - 7.5
DPM++ SDE Karras
Steps: 30 - 40
CFG: 6 - 8.5
DPM++ 2M SDE Karras
Steps: 50+
CFG: 7 - 8
These are just recommendations.
Hires Fix
Settings for all ESRGAN models:
Upscale by
1.5 if resolution is > 512x768
Don't exceed 2.0 (unless you have a beefy rig)
Denoise Strength
0.25 - 0.35
Hires Steps
If sampling steps > 60,
hires steps = half of sampling steps
Otherwise, leave at 0
Extensions
ADetailer
Download here
Neutral Prompt
Download here
Read repo(s) Descriptions for usage guides
Negative Embeddings
Only if you want to remake one of the sample images. Personally, I would avoid using negative embeddings and instead use a simple negative prompt and then add+ or subtract- tokens per new idea. I only use them to speed-up inference during sample generation. That being said, other negative embeddings such as EasyNegative, ect.. are also fine to use with this model.
Checkout my other models
SDXL
SD1.5
Doomer Boomer - https://civarchive.com/models/118247/doomer-boomer
Lomostyle - https://civarchive.com/models/109923/lomostyle
Another Damn Art Model (ADAM) - https://civarchive.com/models/104898/another-damn-art-model-adam
Based Model - https://civarchive.com/models/83991?modelVersionId=89262
Electric Eden - https://civarchive.com/models/64355/electric-eden
Cine Diffusion - https://civarchive.com/models/50000/cine-diffusion
ProjectAIO - https://civarchive.com/models/18428/project-aio
WonderMix - https://civarchive.com/models/15666/wondermix
Experience - https://civarchive.com/models/5952/experience
Elegance - https://civarchive.com/models/5564/elegance
VisionGen - Realism Reborn -https://civarchive.com/models/4834/visiongen-realism
LoRA
Pant Pull Down - https://civarchive.com/models/11126/pant-pull-down-lora
Description
Science n' Dungeons v1
SciStyle v1 + additional fine-tuning on a DnD dataset to combine sci-fi fantasy.
FAQ
Comments (4)
The discord link did not work, but I am curious about your labeling pipeline
I agree. I want more documentation on what species this recognizes.
What the hell dude, the model is astonishingly good, I'm super impressed. It understands everything so well, and works so good. It just works! Pretty good with anatomy, effortlessly does unusual poses without breaking anything. Even hands and fingers are better than average from my experience. I hope you will improve it further. Great job!
This is a very cool model! Excellent flexibility, responsiveness, good anatomy, no gender bias and an incredibly cool expressive old-school illustrative style.
Very good job! Thanks!
Details
Files
Available On (1 platform)
Same model published on other platforms. May have additional downloads or version variants.