Instructions to use dpredrag/Aigencloud with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dpredrag/Aigencloud with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dpredrag/Aigencloud", 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:
- d3d2e0550bc7b44d535d5e99fa08d717df6e3691ec35dfd34940cee89e8b6cad
- Size of remote file:
- 3.44 GB
- SHA256:
- 66fdb1777daa6b15ce88c9c980dd0bd07248ee8c39ae41c140abc3a3e019010f
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