Instructions to use Nambata/dummy_vae_mapi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nambata/dummy_vae_mapi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Nambata/dummy_vae_mapi", 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
- Xet hash:
- 6e76990540765b92fb6ad4dcf3f482cebcc0464f874c7df3e229145eda77959b
- Size of remote file:
- 335 MB
- SHA256:
- ecb8e3c34c668b0cbb4795c8fc4488b27fd530b2a703ca63ab0e8a30edde7d4d
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