Instructions to use iskandre/output5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iskandre/output5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("iskandre/output5", 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:
- cde6d3253ff0a6809070ea56d09b1003e4be395571286d4e7e575685e6f037fd
- Size of remote file:
- 1.72 GB
- SHA256:
- 124e56188f0499132484571ea09ef3108655903261ca1a725f7a5bb996a7cb3e
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