Instructions to use fusing/ddpm-unet-rl-hopper-hor128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fusing/ddpm-unet-rl-hopper-hor128 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fusing/ddpm-unet-rl-hopper-hor128", 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:
- d8e80616618b66877c637ea8596139b2ba9e9f9aba59a370468ed08094b498f5
- Size of remote file:
- 14.8 MB
- SHA256:
- 6ee9974c82f783be1480050b3e68b32d966391578cc27a5aa820b6339dc86464
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