Image-to-Image
Diffusers
Safetensors
English
QwenImageEditPlusPipeline
image-edit
zen
zenlm
hanzo
image-editing
diffusion
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("zenlm/zen-image-edit", dtype=torch.bfloat16, device_map="cuda")
prompt = "Turn this cat into a dog"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
image = pipe(image=input_image, prompt=prompt).images[0]Zen Image Edit
Instruction-following image editing model for targeted modifications and inpainting.
Overview
Built on Zen MoDE (Mixture of Distilled Experts) architecture with 7B parameters.
Developed by Hanzo AI and the Zoo Labs Foundation.
Quick Start
from diffusers import AutoPipelineForText2Image
import torch
model_id = "zenlm/zen-image-edit"
pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe("A serene mountain landscape at sunset, photorealistic").images[0]
image.save("output.png")
API Access
from openai import OpenAI
client = OpenAI(base_url="https://api.hanzo.ai/v1", api_key="your-api-key")
response = client.images.generate(
model="zen-image-edit",
prompt="A serene mountain landscape at sunset",
size="1024px",
)
print(response.data[0].url)
Model Details
| Attribute | Value |
|---|---|
| Parameters | 7B |
| Architecture | Zen MoDE |
| Max Resolution | 1024px |
| License | Apache 2.0 |
License
Apache 2.0
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