Instructions to use ckpt/Cinematic-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ckpt/Cinematic-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("ckpt/Cinematic-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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1d892a11989c2acc887ad48a890af6f5121af001830e0a5f2421668b48c3c887
- Size of remote file:
- 492 MB
- SHA256:
- 3c0ff2cce78fa5f293739468d9f89537075d5822e986d4715fe41fe1c7c267b2
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