ClayCanvas

ClayCanvas - Artistic Style LoRA for Stable Diffusion 1.5

A powerful LoRA (Low-Rank Adaptation) fine-tune of Stable Diffusion 1.5 trained on 12,554 real artworks from the OpenBrush dataset. This model learns authentic artistic styles including oil painting, watercolor, line art, pencil drawing, charcoal, pastel, and more.

Model Details

Training Configuration

Styles Learned

The model was trained on diverse artistic styles:

• Oil Painting - Rich textures, brush strokes, vibrant colors
• Watercolor - Soft washes, flowing colors, transparency
• Pencil Drawing - Detailed sketches, shading, cross-hatching
• Line Art - Clean outlines, minimal, black and white
• Crayon - Waxy texture, vibrant colors, childlike
• Charcoal - Dramatic lighting, smudged textures
• Pastel - Soft colors, powdery texture
• Ink - Bold lines, high contrast
• Impressionism - Light effects, visible brushstrokes

Usage

Option 1: Python with Diffusers

from diffusers import StableDiffusionPipeline
import torch

# Load base model
pipe = StableDiffusionPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5",
    torch_dtype=torch.float16
)
pipe.to("cuda")

# Load ClayCanvas LoRA
pipe.load_lora_weights("satu1234/ClayCanvas")

# Generate image
image = pipe(
    "a tiger in a forest, oil painting",
    num_inference_steps=30,
    guidance_scale=7.5
).images[0]
image.save("output.png")

Option 2: CPU (Slower)

from diffusers import StableDiffusionPipeline
import torch

pipe = StableDiffusionPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5",
    torch_dtype=torch.float32
)
pipe.load_lora_weights("satu1234/ClayCanvas")
pipe.to("cpu")

image = pipe(
    "a Chinese city with pagoda temples, watercolor painting",
    num_inference_steps=100,
    guidance_scale=7.5
).images[0]
image.save("chinese_city.png")

Option 3: Automatic1111 WebUI / Forge

1. Download lora_weights.safetensors from this repo
2. Place in models/LoRA/ folder
3. Use in prompt: <lora:ClayCanvas:1.0>
4. Add style keywords to your prompt

Option 4: ComfyUI

1. Download lora_weights.safetensors
2. Place in models/loras/ folder
3. Add "Load LoRA" node with strength 0.8-1.0

Prompt Guide

Style Keywords

Add these to your prompt for different styles:

Example Prompts

# Oil Painting Landscape
"a mountain landscape at sunset, oil painting, rich textures, vibrant colors, masterpiece"

# Watercolor Portrait
"a woman's face in profile, watercolor painting, soft colors, flowing, artistic"

# Line Art Architecture
"a modern city skyline, line art, clean lines, minimal, black and white"

# Mixed Style
"a forest scene, watercolor background, oil painting on trees, line art details"

# Chinese City
"a beautiful Chinese city with traditional pagoda temples, cherry blossoms, oil painting style, detailed, masterpiece"

# Realistic Scenery with Artistic Touch
"a realistic mountain landscape, watercolor sky, oil painting foreground, line art details"

Recommended Settings

Training Progress

• Dataset: 12,554 real artworks from OpenBrush
• Training Steps: 10,000
• Current Status: Training in progress
• Final Loss: ~0.18

How It Works

1. Base Model: Stable Diffusion 1.5 (1.07B parameters) generates images from text
2. LoRA Adapter: Our trained weights (6.4M parameters) modify the base model to apply artistic styles
3. Result: You get artistic images without retraining the full model

Comparison

License

CC0 (Public Domain) - Based on OpenBrush dataset which is CC0 licensed.

Citation

@misc{claycanvas2026,
  title={ClayCanvas: Artistic Style LoRA for Stable Diffusion 1.5},
  author={Satyam},
  year={2026},
  howpublished={\url{https://huggingface.co/satu1234/ClayCanvas}},
  note={Trained on OpenBrush dataset with 12,554 artworks}
}

Acknowledgments

• OpenBrush Dataset - 75K+ public domain artworks
• Stable Diffusion 1.5 by RunwayML
• Diffusers library
• PEFT for LoRA implementation

Links

• Model Page: https://huggingface.co/satu1234/ClayCanvas
• Base Model: https://huggingface.co/runwayml/stable-diffusion-v1-5
• Dataset: https://huggingface.co/datasets/jaddai/openbrush
• Documentation: https://huggingface.co/docs/diffusers

---

Made with ❤️ by Satyam