Instructions to use gabehubner/vae-256px-8z with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gabehubner/vae-256px-8z with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gabehubner/vae-256px-8z", 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
- Xet hash:
- c135a370f05ef49f1e408b5eb9f82f3e41c31e00cc7c66518b89a514129aaa1c
- Size of remote file:
- 322 MB
- SHA256:
- bccf2a2abec6b609f2a3afe0024dd852e48d6d0dcf82c9677b15062f64bed9c3
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