Instructions to use lightx2v/Qwen-Image-2512-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Qwen-Image-2512-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-2512", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lightx2v/Qwen-Image-2512-Lightning") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use lightx2v/Qwen-Image-2512-Lightning with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
please
Dear LightRx Team,
I am reaching out on behalf of a significant user base, including 6β8 Discord servers, the open-source community, and various content creators.
We are writing to urgently request an 8-step LoRA compatible with Qwen 2512. Currently, the available 4-step LoRA produces quality that is insufficient for Text-to-Image generation. While the 4-step version performs adequately for image editing, it creates unusable results for text-to-image workflows.
The community heavily relied on the high-quality 8-step LoRA provided for previous versions. We would greatly appreciate it if you could release a similar 8-step solution for the current model.
Thank you for listening to community feedback.
they didnt listen
OK, we are training it.
yeeee