Image-to-Image
Diffusers
English
qwen
qwen-image-edit
qwen-image-edit-2511
lora
multi-angle
camera-angles
camera-control
image-editing
gaussian-splatting
fal
Instructions to use fal/Qwen-Image-Edit-2511-Multiple-Angles-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/Qwen-Image-Edit-2511-Multiple-Angles-LoRA 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-Edit-2511", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fal/Qwen-Image-Edit-2511-Multiple-Angles-LoRA") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Absolutely Amazing
#4
by MaximilianWi - opened
Justhad to say this. Tremendously good job with this LORA, not an easy feat at all.
Agreed, works perfectly, and such a nice tool for video frames
A huge thanks to Fal
I find the results quite lackluster. It sort of generates an image from a different angle, but details and especially humans look quite different.
I find the results quite lackluster. It sort of generates an image from a different angle, but details and especially humans look quite different.
Looks spot on to me, so much so i'm impressed every time how well it works ;-)
Maybe using wrong models? or wrong prompt?
Even when throwing it a curveball with a quite a difficult subject and camera aperture



