Diffusers
Safetensors
ConsistencyModelPipeline
generative model
unconditional image generation
consistency-model
Instructions to use openai/diffusers-ct_imagenet64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openai/diffusers-ct_imagenet64 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-ct_imagenet64", 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
Download scheduler/scheduler_config.json from openai/diffusers-ct_imagenet64: direct link, hf CLI and curl.
- Browser
- Download file 244 Bytes
-
https://huggingface.co/openai/diffusers-ct_imagenet64/resolve/main/scheduler/scheduler_config.json
- Command line
-
hf download hf://openai/diffusers-ct_imagenet64/scheduler/scheduler_config.json
-
curl -L -o scheduler_config.json https://huggingface.co/openai/diffusers-ct_imagenet64/resolve/main/scheduler/scheduler_config.json
244 Bytes
| { | |
| "_class_name": "CMStochasticIterativeScheduler", | |
| "_diffusers_version": "0.21.0.dev0", | |
| "clip_denoised": true, | |
| "num_train_timesteps": 201, | |
| "rho": 7.0, | |
| "s_noise": 1.0, | |
| "sigma_data": 0.5, | |
| "sigma_max": 80.0, | |
| "sigma_min": 0.002 | |
| } | |