Instructions to use nitrosocke/Arcane-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/Arcane-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nitrosocke/Arcane-Diffusion", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download scheduler/scheduler_config.json from nitrosocke/Arcane-Diffusion: direct link, hf CLI and curl.
- Browser
- Download file 244 Bytes
-
https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/scheduler/scheduler_config.json
- Command line
-
hf download hf://nitrosocke/Arcane-Diffusion/scheduler/scheduler_config.json
-
curl -L -o scheduler_config.json https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/scheduler/scheduler_config.json
244 Bytes
| { | |
| "_class_name": "LMSDiscreteScheduler", | |
| "_diffusers_version": "0.7.0.dev0", | |
| "beta_end": 0.012, | |
| "beta_schedule": "scaled_linear", | |
| "beta_start": 0.00085, | |
| "clip_sample": false, | |
| "num_train_timesteps": 1000, | |
| "trained_betas": null | |
| } | |