Instructions to use vladmandic/animateface with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vladmandic/animateface with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vladmandic/animateface", 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:
- 38d93430da80369e196ed73b205cb05d0f7169cabc585fd7232867503a27b02e
- Size of remote file:
- 1.67 GB
- SHA256:
- 2724a64ddec065ae015884af2db4ddc40312dca82b3a7c75448397bc50267a1c
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