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:
- b0fa8f0e88e01368e4168119c62a3534524609794336a07ff14e29b8d70758b2
- Size of remote file:
- 1.85 MB
- SHA256:
- 982cfde3e40f103a127eecf0dd816db3a5022567fa52d69b2f889421de775afe
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