SciStyle
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About this version
Model description
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
LomoXL - /model/156743/lomoxl
SD1.5
Revival - /model/149738/revival
Doomer Boomer - /model/118247/doomer-boomer
Lomostyle - /model/109923/lomostyle
Another Damn Art Model (ADAM) - /model/104898/another-damn-art-model-adam
Based Model - /model/83991?modelVersionId=89262
Electric Eden - /model/64355/electric-eden
Cine Diffusion - /model/50000/cine-diffusion
ProjectAIO - /model/18428/project-aio
Eris - /model/21952/eris
WonderMix - /model/15666/wondermix
Refined - /model/8392/refined
Experience - /model/5952/experience
Elegance - /model/5564/elegance
Clarity - /model/5062/clarity
VisionGen - Realism Reborn -/model/4834/visiongen-realism
LoRA
- Pant Pull Down - /model/11126/pant-pull-down-lora