Diffusers
ConsistencyModelPipeline
generative model
unconditional image generation
consistency-model
Instructions to use openai/diffusers-cd_cat256_lpips with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openai/diffusers-cd_cat256_lpips with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("openai/diffusers-cd_cat256_lpips", torch_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": "CMStochasticIterativeScheduler", | |
| "_diffusers_version": "0.17.0.dev0", | |
| "clip_denoised": true, | |
| "num_train_timesteps": 40, | |
| "rho": 7.0, | |
| "s_noise": 1.0, | |
| "sigma_data": 0.5, | |
| "sigma_max": 80.0, | |
| "sigma_min": 0.002 | |
| } | |