Instructions to use dx8152/Qwen-Image-Edit-2511-Gaussian-Splash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dx8152/Qwen-Image-Edit-2511-Gaussian-Splash 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("dx8152/Qwen-Image-Edit-2511-Gaussian-Splash") 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
Dataset size used for training this LoRA
how many images did u use to train this lora?
how many images did u use to train this lora?
This LoRa dataset is only for functional feasibility research, so the amount of data is small, with only 56 datasets.
thank you! keep up the good work.
how many images did u use to train this lora?
This LoRa dataset is only for functional feasibility research, so the amount of data is small, with only 56 datasets.
Hi DX! Does '56 datasets' mean you only use 56 data samples, like 56 3DGS data? Thank you!
how many images did u use to train this lora?
This LoRa dataset is only for functional feasibility research, so the amount of data is small, with only 56 datasets.
Hi DX! Does '56 datasets' mean you only use 56 data samples, like 56 3DGS data? Thank you!
Each set of data has two inputs and one output. There are a total of 56 sets of data.