Vrizzo/indian-art-sd-model

🎨 Indian Art Stable Diffusion Model

Generate beautiful traditional Indian art styles using simple text prompts. Fine-tuned from Stable Diffusion v1.5 on Indian cultural art themes.

🖼️ Sample Outputs

✅ What This Model Is Good At

• Madhubani / Mithila folk paintings
• Warli tribal art
• Rangoli festival designs
• Mughal miniature painting style
• Tanjore / Thanjavur classical style
• Pattachitra cloth paintings
• Indian festival scenes (Diwali, Holi, Ganesh Chaturthi)
• Traditional dancers (Bharatanatyam, Kathak)

🚀 How To Use It

In Google Colab (Easiest)

from diffusers import StableDiffusionPipeline
import torch

pipe = StableDiffusionPipeline.from_pretrained(
    "Vrizzo/indian-art-sd-model",
    torch_dtype=torch.float16
).to("cuda")

image = pipe(
    "Madhubani painting of a peacock, intricate patterns, vibrant colors",
    negative_prompt="blurry, low quality, distorted",
    num_inference_steps=30,
    guidance_scale=7.5
).images[0]

image.save("output.png")

🌟 Best Prompts To Try

Style	Prompt
Madhubani	Madhubani painting of peacock, intricate patterns, Bihar folk art
Warli	Warli tribal art, village harvest scene, geometric figures, white on red
Rangoli	Diwali rangoli design, symmetrical mandala, lotus motif, vibrant colors
Miniature	Mughal miniature painting, royal court scene, gold accents, fine detail
Tanjore	Thanjavur painting, goddess Lakshmi, gold foil emboss, gemstone colors

⚙️ Model Details

• Base model: runwayml/stable-diffusion-v1-5
• Image size: 512×512
• Recommended steps: 25–40
• Recommended guidance scale: 7–9

⚠️ Limitations

• Works best with art style keywords included in the prompt
• Photorealistic human faces are not its strength
• Best results at 512×512 resolution