Instructions to use dn6/RFDiffusion-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dn6/RFDiffusion-3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dn6/RFDiffusion-3", 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": "RFDiffusionScheduler", | |
| "_diffusers_version": "0.37.0.dev0", | |
| "auto_map": { | |
| "AutoModel": "model.RFDiffusionScheduler" | |
| }, | |
| "num_timesteps": 200, | |
| "sigma_data": 16.0, | |
| "s_min": 4e-4, | |
| "s_max": 160.0, | |
| "p": 7.0, | |
| "gamma_0": 0.6, | |
| "gamma_min": 1.0, | |
| "noise_scale": 1.003, | |
| "step_scale": 1.5 | |
| } | |