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:
- 9a14fef7dfb98b4b0b8a78fa79183c571251c66ffe3725e608fef08cb0624d07
- Size of remote file:
- 1.51 GB
- SHA256:
- 1eca12779c5f9d29ad050424415378dbe7a7132251ce6f153e8c67e0f573a03d
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