Instructions to use google/ncsnpp-bedroom-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use google/ncsnpp-bedroom-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("google/ncsnpp-bedroom-256", 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_config.json from google/ncsnpp-bedroom-256: direct link, hf CLI and curl.
- Browser
- Download file 211 Bytes
-
https://huggingface.co/google/ncsnpp-bedroom-256/resolve/11eb3d898ff2c7c804c44cac7579402cd7ade0f6/scheduler_config.json
- Command line
-
hf download hf://google/ncsnpp-bedroom-256@11eb3d898ff2c7c804c44cac7579402cd7ade0f6/scheduler_config.json
-
curl -L -o scheduler_config.json https://huggingface.co/google/ncsnpp-bedroom-256/resolve/11eb3d898ff2c7c804c44cac7579402cd7ade0f6/scheduler_config.json
211 Bytes
| { | |
| "_class_name": "ScoreSdeVeScheduler", | |
| "_diffusers_version": "0.1.0", | |
| "correct_steps": 1, | |
| "num_train_timesteps": 2000, | |
| "sampling_eps": 1e-05, | |
| "sigma_max": 380, | |
| "sigma_min": 0.01, | |
| "snr": 0.075 | |
| } | |