Instructions to use OPPOer/Qwen-Image-Pruning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OPPOer/Qwen-Image-Pruning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OPPOer/Qwen-Image-Pruning", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
models in subfolders
#8
by liutyi - opened
This way to store models (Author/(Model)Model-Group/(Sub-folder)Model) crate some issues like this one with SD.Next integration . Just want to ask if it is possible those (Qwen prunning and Qwen Pruing Edit) models be stored in "classic HF way" Author/Model? Each Model variant as a separate model..
Got it, we'll consolidate everything in the next couple of days and update accordingly. Appreciate the reminder.