Instructions to use TornikeO/Future-Diffusion16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TornikeO/Future-Diffusion16 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TornikeO/Future-Diffusion16", 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:
- 7fccd60317075d5969f2142c862e91f9b0d754afe80848ddac5b67b99354061a
- Size of remote file:
- 681 MB
- SHA256:
- 158a32928928a2e1fb6dddf413f2b7d0f8722ca5e9655300c95c13654b636f3d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.