Instructions to use valhalla/mad_max_diffusion-sd2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use valhalla/mad_max_diffusion-sd2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("valhalla/mad_max_diffusion-sd2", 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:
- 8d9d71974bb06afbee34f8469a73c0a887854a3a955dd1f3b6110d8311e559b7
- Size of remote file:
- 4.74 MB
- SHA256:
- 528ef5f8c16869f9605f1036ac680ae8e54365678fd9fbf1bb8ff6d13a9fd2b6
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