Instructions to use fusing/ddpm-unet-rl-hopper-hor512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fusing/ddpm-unet-rl-hopper-hor512 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-hor512", 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
| { | |
| "_class_name": "TemporalUnet", | |
| "_diffusers_version": "0.0.4", | |
| "training_horizon": 512, | |
| "dim": 32, | |
| "dim_mults": [1, 4, 8], | |
| "predict_epsilon": false, | |
| "clip_denoised": true, | |
| "transition_dim": 14, | |
| "cond_dim": 3 | |
| } | |