Instructions to use Anzhc/MS-LC-EQ-D-VR_VAE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Anzhc/MS-LC-EQ-D-VR_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("Anzhc/MS-LC-EQ-D-VR_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
- Xet hash:
- b38e0950ee8cf939bcb79defb8b0e04e1a6615a7b025d1e9af1ab41841943aa9
- Size of remote file:
- 335 MB
- SHA256:
- b1e3e2cad702f50df8fe26bf63a928f364aebc6d67610390248807746fee2d45
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