deepgenteam/DeepGen-1.0-diffusers

pip install torch diffusers transformers safetensors einops accelerate huggingface_hub
# Flash Attention (recommended)
pip install flash-attn --no-build-isolation

import torch
from diffusers import DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained(
    "deepgenteam/DeepGen-1.0-diffusers",
    torch_dtype=torch.bfloat16,
    trust_remote_code=True,
)
pipe.to("cuda")

# Optional: enable CPU offload for GPUs with limited memory (< 24GB)
# pipe.enable_model_cpu_offload()

result = pipe(
    prompt="a racoon holding a shiny red apple over its head",
    height=512, width=512,
    num_inference_steps=50,
    guidance_scale=4.0,
    seed=42,
)
result.images[0].save("output.png")

from PIL import Image

source_image = Image.open("guitar.png").convert("RGB")
result = pipe(
    prompt="Take a photo of this guitar placed on a sandy beach with the sunset in the background.",
    image=source_image,
    height=512, width=512,
    num_inference_steps=50,
    guidance_scale=4.0,
    seed=42,
)
result.images[0].save("edited.png")

DeepGen-1.0-diffusers/
├── transformer/          # SD3 DiT weights (safetensors)
├── vae/                  # AutoencoderKL weights
├── connector/            # SCB Connector weights + config
├── scheduler/            # FlowMatchEulerDiscreteScheduler config
├── tokenizer/            # Qwen2.5-VL tokenizer
├── prompt_template.json  # Prompt formatting template
├── model_index.json      # Model metadata
└── deepgen_pipeline.py   # Self-contained pipeline script

@article{wang2026deepgen,
  title={DeepGen 1.0: A Lightweight Unified Multimodal Model for Advancing Image Generation and Editing},
  author={Wang, Dianyi and Li, Ruihang and Han, Feng and Ma, Chaofan and Song, Wei and Wang, Siyuan and Wang, Yibin and Xin, Yi and Liu, Hongjian and Zhang, Zhixiong and others},
  journal={arXiv preprint arXiv:2602.12205},
  year={2026}
}