Instructions to use Superklok/SuperklokStyleLoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Superklok/SuperklokStyleLoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3.5-large", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Superklok/SuperklokStyleLoRA") prompt = "Superklok Style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
A production-grade style fine-tuning model trained natively on Stable Diffusion 3.5 Large to reproduce the Superklok Art Style. It flawlessly reproduces ultra-saturated, neon-green circuit board backgrounds, copper soldering points, glossy hardware capacitors, and authentic analog horizontal CRT television monitor scanlines!
π License & Mandatory Attribution
This repository is distributed under the SUPERKLOK LABS UNIFIED PUBLIC ASSET LICENSE v1.0:
100% Free for Commercial Use: You are fully permitted to use this LoRA, test images, and configurations to generate commercial artwork.
Mandatory Credit: You must credit Superklok Labs by linking to or tagging one of our official handles (Twitter(X) or Instagram) whenever you publish content created or upscaled with this asset.
π΅ The Ultimate Commercial Core
Unlike standard community assets tied to restrictive non-commercial licenses, this entire architecture is completely free for commercial deployment.
Indie Game Developers: Generate menus, title screens, and concept art locally.
Content Creators: Automate flashy and unique marketing image generation streams.
IP Creators: Monetize your original marketing images and visual outputs with zero platform overhead.
π Model Technical Details & Parameters
Activation Trigger Word:
Superklok StyleRecommended Weight:
0.5 - 0.8(Style models naturally thrive at slightly lower weights to preserve creative composition flexibility)Native Trained Resolution: 1344x768 (Landscape centered-crop dataset layout)
Dataset Density: 120 hand-selected art style images at 20 processing iterations per file (2,700 total training steps)
Final Loss Value:
0.1404(Textbook-perfect score for intricate style retention without rigidity)
π οΈ Open-Source Training & Premium Workflows
SuperklokStyleLoRA was created with the help of the ComfyUImarketing engine, specializing in turning primitive MS Paint drawings combined with text prompts into highly detailed production assets.
π Want to train it yourself? Get the raw 120-image dataset, local portable ComfyUI scripts, and
captioner.pysetup guides on our GitHub Repository.π° Want the definitive setup? Purchase our production-grade Premium ComfyUImarketing Automation Workflow directly via our Gumroad Store.
πΌ Hire Superklok Labs for Enterprise Solutions
If you need custom-engineered generation pipelines, bespoke brand style LoRAs, hyper-speed rendering setups, or enterprise-optimized local ComfyUI environments, let's build it together:
πΌ Hire on Upwork
β‘ Hire on Contra
- Downloads last month
- 22
Model tree for Superklok/SuperklokStyleLoRA
Base model
stabilityai/stable-diffusion-3.5-large