Instructions to use nitrosocke/Future-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/Future-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("nitrosocke/Future-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
- Draw Things
- DiffusionBee

- Xet hash:
- cb5229771591ce75dccb20bbf8045fbab0a9df8b1c73ebc56f97fb3d0726aeaa
- Size of remote file:
- 2.89 MB
- SHA256:
- 53e0e86ff93203dc2531439c51f95e7d040f8b31838236ec96259954b7297d1e
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