Instructions to use nitrosocke/archer-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/archer-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/archer-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
- Draw Things
- DiffusionBee

- Xet hash:
- ad2d09193b22cf18e9b0b64324e4cae4ce4c56a5ce80ee41fd2b50bfbeabe909
- Size of remote file:
- 1.33 MB
- SHA256:
- 003a638a28fbbc4d6c5330ce7b8768fe09fcdf927b8782e2111bfbfc58f13469
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