Instructions to use jzli/DreamShaper-3.3-baked-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jzli/DreamShaper-3.3-baked-vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jzli/DreamShaper-3.3-baked-vae", 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
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Check out the documentation for more information.
This is DreamShaper 3.3 with vae baked in, so you don't need to add vae when running it
Read more about this model here: https://civitai.com/models/4384/dreamshaper
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