Image-to-Image
Diffusers
Pruna AI
qwen
qwen-image
image-editing
object-removal
inpainting
lora
distilled
few-step
Instructions to use PrunaAI/P-Q-Image-2.1-Remove-Object with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PrunaAI/P-Q-Image-2.1-Remove-Object 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("Qwen/Qwen-Image-2.1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("PrunaAI/P-Q-Image-2.1-Remove-Object") 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] - Pruna AI
How to use PrunaAI/P-Q-Image-2.1-Remove-Object with Pruna AI:
from pruna import PrunaModel pip install -U diffusers transformers accelerate
from pruna import PrunaModel import torch from diffusers.utils import load_image # switch to "mps" for apple devices pipe = PrunaModel.from_pretrained("Qwen/Qwen-Image-2.1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("PrunaAI/P-Q-Image-2.1-Remove-Object") 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
- Local Apps Settings
- Draw Things
Download examples/L8_result.jpg from PrunaAI/P-Q-Image-2.1-Remove-Object: direct link, hf CLI and curl.
- Browser
- Download file 255 kB
-
https://huggingface.co/PrunaAI/P-Q-Image-2.1-Remove-Object/resolve/main/examples/L8_result.jpg
- Command line
-
hf download hf://PrunaAI/P-Q-Image-2.1-Remove-Object/examples/L8_result.jpg
-
curl -L -o L8_result.jpg https://huggingface.co/PrunaAI/P-Q-Image-2.1-Remove-Object/resolve/main/examples/L8_result.jpg
255 kB

- Xet hash:
- d3c0571d736a0c258dfd7d3da4a8104c8fbe5ad1b6450008ccad335820489df9
- Size of remote file:
- 255 kB
- SHA256:
- eb32d08f0f4844781c96b3e6294cc36030af30c8f491e733ad6c3ce143a5cc07
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