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
- Draw Things
- DiffusionBee
- Xet hash:
- 1dfb26d6283019ea69cd62014c8bd9fc214fb6cb4abc26b03c08fe20f3b18158
- Size of remote file:
- 1.36 GB
- SHA256:
- a56089bb13e4a5f0fb4455f301346f577f92f8fe97b8beb996fdf9011724d3a8
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