Instructions to use daniel-comet/stevefussion-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use daniel-comet/stevefussion-v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("daniel-comet/stevefussion-v3", 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:
- 1e22b69581651af8df070e289071653d9c984eba27900e02bea1e42ff9001a33
- Size of remote file:
- 492 MB
- SHA256:
- 23eed8da9f7eff2b5c794de96b3de391aac4b7dcee998afbc1ad41887144006a
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