Instructions to use latent-consistency/lcm-sdxl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use latent-consistency/lcm-sdxl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("latent-consistency/lcm-sdxl", 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
can't work in "AUTOMATIC1111/stable-diffusion-webui"
#7
by bobby20180331 - opened
Great work.
I used the model in "AUTOMATIC1111/stable-diffusion-webui".However errors as followed .
NansException: A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.
after i setting "Upcast cross attention layer to float32" erros still exist. no matter fp16(5GB ) or standard verion (10GB) is choosen. any suggestions?
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