Instructions to use cdefghijkl/jalanlurus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cdefghijkl/jalanlurus with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cdefghijkl/jalanlurus", 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:
- e78beed181df38e7a810daa613badedc617d2caab109f4562c80909ad100e049
- Size of remote file:
- 335 MB
- SHA256:
- 330033d641ed6aa8655fbc240af6c2b7673a6f2e5213e92353cccdafc3279c4c
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