Qwen-Image-Edit-2511-INT4-Diffusers
This repository contains a Diffusers-compatible NF4 (4-bit NormalFloat) quantized version of the Qwen/Qwen-Image-Edit-2511 model.
Model Overview
- Base Model: Qwen/Qwen-Image-Edit-2511
- Quantization: NF4 4-bit with double quantization on the transformer component.
- Compute dtype:
torch.bfloat16(weights stored in 4-bit, math done in BF16). - Pipeline Compatibility: Hugging Face Diffusers (
QwenImageEditPlusPipeline). - License: Apache 2.0 (Inherited from upstream base model).
- Weight Format: PyTorch
.bin(bitsandbytes NF4 tensors require pickle serialization).
For detailed model architecture, training details, and evaluations, please refer to the official Qwen/Qwen-Image-Edit-2511 repository.
Usage Example
import torch
from diffusers import BitsAndBytesConfig, QwenImageEditPlusPipeline
from diffusers.utils import load_image
# Runtime NF4 quantization (recommended approach for best compatibility)
quant_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16,
bnb_4bit_use_double_quant=True,
)
pipe = QwenImageEditPlusPipeline.from_pretrained(
"Qwen/Qwen-Image-Edit-2511",
quantization_config=quant_config,
torch_dtype=torch.bfloat16,
)
pipe.enable_model_cpu_offload()
input_image = load_image("https://example.com/input.jpg")
output_image = pipe(
prompt="A realistic tattoo on forearm",
image=[input_image],
num_inference_steps=20,
guidance_scale=4.5,
height=1024,
width=768,
).images[0]
output_image.save("output.png")
License
This model is released under the Apache License 2.0, consistent with the original Qwen/Qwen-Image-Edit-2511 release.