Instructions to use mohdasif81/Qwen-Image-Edit-Rapid-AIO-V19 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mohdasif81/Qwen-Image-Edit-Rapid-AIO-V19 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mohdasif81/Qwen-Image-Edit-Rapid-AIO-V19", 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] - Notebooks
- Google Colab
- Kaggle
Diffusers-compatible transformer weights extracted from Phr00t/Qwen-Image-Edit-Rapid-AIO-NSFW-V19 for 4-step accelerated Qwen Image Edit inference.
Quick Start with Diffusers🧨
pip install -U torch transformers diffusers
import torch
from diffusers.models import QwenImageTransformer2DModel
from diffusers import QwenImageEditPlusPipeline
from diffusers.utils import load_image
transformer = QwenImageTransformer2DModel.from_pretrained(
"prithivMLmods/Qwen-Image-Edit-Rapid-AIO-V19",
torch_dtype=torch.bfloat16
)
pipeline = QwenImageEditPlusPipeline.from_pretrained(
"Qwen/Qwen-Image-Edit-2511",
transformer=transformer,
torch_dtype=torch.bfloat16
)
pipeline.to("cuda")
image1 = load_image("grumpycat.png")
prompt = "turn the cat into an orange cat"
inputs = {
"image": [image1],
"prompt": prompt,
"generator": torch.manual_seed(42),
"true_cfg_scale": 1.0,
"negative_prompt": " ",
"num_inference_steps": 4,
"guidance_scale": 1.0,
"num_images_per_prompt": 1,
}
output = pipeline(**inputs)
output_image = output.images[0]
output_image.save("output_image_edit_plus.png")
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Model tree for mohdasif81/Qwen-Image-Edit-Rapid-AIO-V19
Base model
Qwen/Qwen-Image-Edit-2511 Finetuned
Phr00t/Qwen-Image-Edit-Rapid-AIO