Instructions to use WALIDALI/marimrev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/marimrev with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WALIDALI/marimrev", 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:
- efdaf2013beae293aa6ca2a2f56dab979e6c7370479136905ef580cc74e92c51
- Size of remote file:
- 246 MB
- SHA256:
- e94ba634e6395a4d57a1bf1fe6f077a9cfbf6e197026f7a259741206cfd2217c
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