Instructions to use maxmarcon/klimt-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maxmarcon/klimt-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("maxmarcon/klimt-diffusion", 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
- Xet hash:
- 0e187a768ae40e4e1f4039d5aa1eedc38c89a7232e43f46f77ce62cf759c7821
- Size of remote file:
- 910 MB
- SHA256:
- 601eb9b17b69cba262271c61d22cccb948c05c8282b70073a06b36d51ed6bb53
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.