Text-to-Image
Diffusers
English
lora
stable-diffusion-xl
style
comic
comic-book
ink
halftone
illustration
cartoon
vintage
retro
primary-colors
graphic-novel
artistic
realistic
color-grading
style-lora
Instructions to use strkyyy/comic-ink-halftone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use strkyyy/comic-ink-halftone 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-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("strkyyy/comic-ink-halftone") prompt = "c0m1cink, a superhero standing on a rooftop at night" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| license: openrail++ | |
| language: | |
| - en | |
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| base_model: stabilityai/stable-diffusion-xl-base-1.0 | |
| instance_prompt: c0m1cink | |
| tags: | |
| - lora | |
| - stable-diffusion-xl | |
| - text-to-image | |
| - diffusers | |
| - style | |
| - comic | |
| - comic-book | |
| - ink | |
| - halftone | |
| - illustration | |
| - cartoon | |
| - vintage | |
| - retro | |
| - primary-colors | |
| - graphic-novel | |
| - artistic | |
| - realistic | |
| - color-grading | |
| - style-lora | |
| widget: | |
| - text: "c0m1cink, a superhero standing on a rooftop at night" | |
| - text: "c0m1cink, a fierce dragon breathing fire" | |
| - text: "c0m1cink, a detective examining a clue" | |
| # SDXL LoRA: Retro Comic Book Ink & Halftone Style | |
| ## What it does | |
| This LoRA injects a classic comic book style into your artwork, featuring bold black outlines, dramatic cross-hatching, and Ben-Day halftone dot shading for an authentic vintage print look with slight color misregistration. | |
| ## How to use | |
| Trigger the effect by using 'c0m1cink' in your prompt. A suggested strength of 0.85 typically works well, but you can adjust it based on desired intensity. Use a sampler and settings that work for comic art, such as DDIM at around 30 steps. | |
| ## Best for | |
| - Superhero scenes | |
| - Fierce dragons and mythical creatures | |
| - Detective stories with mystery elements | |
| - Futuristic cityscapes with robots or mechs | |
| - Pirate adventures on the high seas | |
| ## Tips | |
| Use punchy primary colors to enhance the comic book feel. Experiment with different strengths of 'c0m1cink' for varying levels of comic stylization. | |
| ## Example Prompts | |
| ``` | |
| c0m1cink A dramatic portrait of a superhero in shadowy alleyway, rain-slicked cobblestones and noir lighting. | |
| ``` | |
| ``` | |
| c0m1cink An architectural scene with towering skyscrapers in the background, a bustling cityscape at sunset, warm golden light. | |
| ``` | |
| ``` | |
| c0m1cink Vintage comic book illustration style for an object - a sleek sports car, sharp lines and primary colors against a halftone backdrop. | |
| ``` | |
| ``` | |
| c0m1cink A dynamic action scene of a hero leaping through the air, dramatic movement with bold ink outlines and vibrant color accents. | |
| ``` | |
| ``` | |
| c0m1cink Moody comic book page depicting an eerie forest at night, moonlight filtering through branches, shadows and fog creating tension. | |
| ``` | |
| ``` | |
| c0m1cink Abstract pattern inspired by Ben-Day dots and halftone shading, vivid colors swirling in a psychedelic, retro-futuristic design. | |
| ``` | |
| ## Trigger word | |
| Activate with `c0m1cink`. Recommended strength: **0.9**. | |
| ## Showcase | |
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| ## Usage with `diffusers` | |
| ```python | |
| from diffusers import AutoPipelineForText2Image | |
| import torch | |
| pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16).to("cuda") | |
| pipe.load_lora_weights("strkyyy/comic-ink-halftone") | |
| image = pipe("c0m1cink, your prompt", num_inference_steps=30).images[0] | |
| ``` | |