Instructions to use Jiabooo/diffusionsat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jiabooo/diffusionsat with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jiabooo/diffusionsat", 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:
- 1873fd311ec8dc4a4104bf9d9b5177072e0182a3a37da48e217afd2f2ce0e121
- Size of remote file:
- 1.76 GB
- SHA256:
- 1ce3e7afb16603a36299de51d81f898f2e125b0372254a901feb44f2d3017db7
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