Notice โ€” Modified re-upload: This repository is ISLAM-PO/Glitch-Img-1.0, a renamed re-upload based on Qwen/Qwen-Image-2.1. Modified files: README.md (renaming, repo-ID updates, attribution notes). All model weights and configs are unchanged from the original. Built with Qwen. Original work remains under the Qwen Research License Agreement, non-commercial use only. See NOTICE for required attribution.

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Introduction

We are excited to publish Glitch-Img-1.0, a renamed re-upload based on Qwen-Image-2.1, a unified text-to-image generation and image editing model in the Qwen family. Built with Qwen. Base model: Qwen/Qwen-Image-2.1. With just 7B parameters in its visual generation component (32 Single-Stream DiT layers), Glitch-Img-1.0 balances generation quality, inference efficiency, and versatility.

Four key improvements define this release:

  • Compact and Efficient โ€” A lightweight architecture with mixed-granularity attention and prefix KV cache reuse delivers strong image quality at low computational cost.
  • Native Transparency, Unified Creation and Editing โ€” Generate regular or transparent (RGBA) images from text, edit transparent layers, and extract subjects from photographsโ€”all in one model.
  • Versatile Editing โ€” Support up to 10 reference images, specify local edits via circles, painted annotations, or separate masks, and preserve identity for people and products.
  • Realistic Textures and Refined Aesthetics โ€” Improved typography, portrait lighting, and fine details for more visually compelling results.

For more details, see the GitHub repo and Blog.

Quick Start

Installation

pip install torch>=2.4.0
pip install transformers>=5.17
pip install git+https://github.com/huggingface/diffusers
pip install accelerate pillow

Text-to-Image

import torch
from diffusers import QwenImage21Pipeline

pipe = QwenImage21Pipeline.from_pretrained(
    "ISLAM-PO/Glitch-Img-1.0", torch_dtype=torch.bfloat16
).to("cuda")

image = pipe(
    prompt="A neon shop sign that reads \"GLITCH IMG 1.0\", rainy night, reflections on wet pavement",
    width=2048, height=2048,
    num_inference_steps=40,
    generator=torch.Generator("cuda").manual_seed(42),
).images[0]

image.save("t2i_example.png")

Image Editing

import torch
from PIL import Image
from diffusers import QwenImage21Pipeline

pipe = QwenImage21Pipeline.from_pretrained(
    "ISLAM-PO/Glitch-Img-1.0", torch_dtype=torch.bfloat16
).to("cuda")

input_image = Image.open("input.png")

image = pipe(
    prompt="Change the background to a sunset beach",
    image=input_image,
    num_inference_steps=40,
    generator=torch.Generator("cuda").manual_seed(42),
).images[0]

image.save("edit_example.png")

Transparent Image Generation (RGBA)

Use the recommended prompt format for transparent images:

image = pipe(
    prompt="This is an RGBA image with transparency. A cute cartoon dragon sticker. The image has alpha channel and the background is transparent.",
    width=2048, height=2048,
    num_inference_steps=40,
    generator=torch.Generator("cuda").manual_seed(42),
).images[0]

image.save("transparent_example.png")

Supported Aspect Ratios

aspect_ratios = {
    "1:1":  (2048, 2048),
    "4:3":  (2400, 1792),
    "3:4":  (1792, 2400),
    "3:2":  (2528, 1696),
    "2:3":  (1696, 2528),
    "16:9": (2752, 1536),
    "9:16": (1536, 2752),
}

Memory Optimization

pipe = QwenImage21Pipeline.from_pretrained(
    "ISLAM-PO/Glitch-Img-1.0", torch_dtype=torch.bfloat16
)
pipe.enable_model_cpu_offload()

Showcase

Native transparent image generation

Group photograph generated from six portrait references

Text rendering

License

This model is licensed under the Qwen Research License Agreement. Non-commercial use only.

Attribution: Qwen is licensed under the Qwen RESEARCH LICENSE AGREEMENT, Copyright (c) 2026 Hangzhou Tongyi Laboratory Technology Co., Ltd. All Rights Reserved. This re-upload (ISLAM-PO/Glitch-Img-1.0) is Built with Qwen and based on Qwen/Qwen-Image-2.1. For commercial use, request a license at model-business@notice.qwencloud.com.

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