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", torch_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
- Xet hash:
- b8f9755d5a140f1697fa0ac70c8d7f13d9b0a8edd9e62095cad451b955694d41
- Size of remote file:
- 3.44 GB
- SHA256:
- 4be61be9736230849d5692d75ad39ad28bc42f4777f3f53206114ed1c49a400a
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