Instructions to use TornikeO/Future-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TornikeO/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("TornikeO/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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c8348ed554d377a56e0cc4d346d25b48172ed0e34cd128cf433198fc2a26c9eb
- Size of remote file:
- 681 MB
- SHA256:
- d59601ed20337dbf7de34db427bff8c780dddd5984fd950299e82eb540a14953
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