Instructions to use codemichaeld/sd_vae_01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemichaeld/sd_vae_01 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("codemichaeld/sd_vae_01", 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:
- a9b0956175fae4f1173c5151befd35bdf7e632f434b1e78ffd98b50c9fff71fd
- Size of remote file:
- 83.7 MB
- SHA256:
- ec23830be22e3461bd1a47389f90a20f27b0f6041837bebeb033f682ddbd5043
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