Instructions to use ByteDance/SDXL-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/SDXL-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("ByteDance/SDXL-Lightning", 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
Training code
Very interesting work! I wonder if the authors plan to release the training code as well?
We are currently not planning on releasing the training code.
Hi author, Could you mind releasing a version of LoRAs for A1111 stable-diffusion-webui?
Unfortunate that we aren't getting training code, but I get why there may be issues or extra challenges adapting it for public release. Thanks for the transparency.
Hi author, Could you mind releasing a version of LoRAs for A1111 stable-diffusion-webui?
Hum, does A1111 have a different format? does our checkpoint not just work?
Hi author, Could you mind releasing a version of LoRAs for A1111 stable-diffusion-webui?
Hum, does A1111 have a different format? does our checkpoint not just work?
A1111 need a single safetensor file containing the whole model, including unet, vae, tokenizer, etc. Check sdxl's safetensor file example https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/sd_xl_base_1.0.safetensors