🌿 Craftly-Image-Turbo (12.8B)

⚡ Ultra-Fast High-Fidelity Diffusion Transformer by Md Mushfiqur Rahim

Craftly-Image-Turbo is a state-of-the-art distilled 8-step visual synthesis foundation model engineered for real-time inference, photorealistic detail, anime aesthetic excellence, and complex prompt execution.

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🎨 Showcase Gallery

🌸 Anime Girl in Nature	🌿 4K Macro Mossy Forest	🏛️ Minimalist Travertine Pavilion

(Explore the full 50-image 4K showcase gallery in the 📁 images/ directory).

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🚀 One-Click Interactive Studios (Colab, Kaggle, Marimo)

You can launch and generate images immediately using any of our ready-to-run studios in the notebooks/ directory:

1. 🟡 Google Colab Studio

• Notebook: notebooks/CRAFTLY_GOOGLE_COLAB.ipynb
• Features: Interactive UI sliders, curated prompt presets (Anime Girl, 4K Nature, Minimalist Zen, Cyberpunk City), and automatic image download to your computer.
• Hardware: Runs smoothly on free T4 GPU, V100, L4, or A100.

2. 🔵 Kaggle Studio

• Notebook: notebooks/CRAFTLY_KAGGLE.ipynb
• Features: Optimized for Kaggle Dual T4 or P100 GPUs, automatic VRAM clearing, batch image generation loop, and output to /kaggle/working/.

3. 🟣 Marimo Reactive Web App

• Script: notebooks/CRAFTLY_MARIMO.py
• Notebook: notebooks/CRAFTLY_MARIMO_JUPYTER.ipynb
• Features: Full reactive browser app with marimo run. Real-time text prompt area, step sliders, resolution selector, and instant reactive image generation.

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💻 Python Quickstart

import torch
from diffusers import DiffusionPipeline

REPO_ID = "CraftlyrobotMushfiqur/testy"
device = "cuda" if torch.cuda.is_available() else "cpu"
dtype = torch.bfloat16 if torch.cuda.is_available() and torch.cuda.is_bf16_supported() else torch.float16

# 1. Load sovereign pipeline
pipe = DiffusionPipeline.from_pretrained(
    REPO_ID,
    custom_pipeline="pipeline_craftly",
    torch_dtype=dtype,
    trust_remote_code=True
).to(device)

# 2. Ultra-Fast 8-Step Synthesis
prompt = (
    "A breathtaking masterpiece of a beautiful anime girl standing in a sunlit lush green forest meadow, "
    "gentle breeze fluttering her long silky hair and delicate white dress, glowing cherry blossoms and emerald leaves "
    "floating in the air, crystal clear sparkling stream beside her, Makoto Shinkai and Studio Ghibli aesthetic, "
    "cinematic volumetric golden hour sunbeams, radiant expressive eyes, peaceful smile, vibrant 4k anime wallpaper, hyper-detailed"
)

with torch.inference_mode():
    image = pipe(
        prompt=prompt,
        num_inference_steps=8,
        guidance_scale=0.0,
        width=1024,
        height=1024
    ).images[0]

image.save("craftly_output.png", quality=95)
print("✅ Saved to craftly_output.png")

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🏗️ Architecture Specifications

• Pipeline Class: CraftlyImagePipeline
• Transformer Diffusion Backbone: CraftlyImageTransformer2DModel (28 Layers, 48 Attention Heads, 64-channel Latent Input)
• Text Conditioning Backbone: CraftlyVisionModel (36 Layers, 2560 Hidden Dim)
• Latent Autoencoder: 16-channel Spatial VAE
• Denoising Trajectory: Flow-Matching Euler Discrete Scheduler (Optimized 8-step Distillation)
• Native Resolution: 1024×1024 pixels

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⚖️ Citation & Attribution

@article{craftlyimageturbo2026,
  title={Craftly-Image-Turbo: High-Velocity Visual Generation via Distilled Flow-Matching},
  author={Md Mushfiqur Rahim and Craftly AI Research Team},
  year={2026},
  publisher={Hugging Face}
}

📐 Sovereign Architecture Computation Graph

Computation graph rendered from the real module graph (CraftlyTransformerBlock x28, CraftlyTextFusionBlock x2, CraftlyVisionEncoder x36). Open craftly_model_viewer.html for the interactive version.

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