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 text_encoder/pytorch_model.bin from nitrosocke/Arcane-Diffusion: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://nitrosocke/Arcane-Diffusion/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 68eddb31dab291d662ff36bc62303872ac8821416dcd99dd7f3093855fc689c1
- Size of remote file:
- 492 MB
- SHA256:
- 4416d22ae7ebaaad243f084b970befb639c80d9ac812e18848f98f538f11e238
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