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 Settings
- Draw Things
- DiffusionBee
Download archer-diffusion-samples.png from nitrosocke/archer-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 1.33 MB
-
https://huggingface.co/nitrosocke/archer-diffusion/resolve/refs%2Fpr%2F1/archer-diffusion-samples.png
- Command line
-
hf download hf://nitrosocke/archer-diffusion@refs/pr/1/archer-diffusion-samples.png
-
curl -L -o archer-diffusion-samples.png https://huggingface.co/nitrosocke/archer-diffusion/resolve/refs%2Fpr%2F1/archer-diffusion-samples.png
1.33 MB

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