Instructions to use krasnova/ddpm_afhq_64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use krasnova/ddpm_afhq_64 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krasnova/ddpm_afhq_64", 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:
- 892566416dc9487985bf08c020b00e2c813801b78397f94a5ea3450860a2f8ec
- Size of remote file:
- 74.3 MB
- SHA256:
- 287ae0e91c448934f1f2a81060a0229d1e3d06c3164ebc12d6e4ee5ec73b9b79
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