Instructions to use acul3/aculstabble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use acul3/aculstabble with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("acul3/aculstabble", 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:
- 6dcd35dd29a45e1d7e380c821fea98cc33a0d3085d453a6d45c47ca165bd16da
- Size of remote file:
- 492 MB
- SHA256:
- ec7b3499a248c2a4f284c01cce515f74f7b814bfa947f54ce3f325d6dc27a5bd
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