Instructions to use schrum2/MarioDiffusion-MLM-negative0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MLM-negative0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("schrum2/MarioDiffusion-MLM-negative0", 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
- Xet hash:
- 62ac03065d0feea1121a100e3ac166325f7c47b62ac64ed33e391802809a8f17
- Size of remote file:
- 2.17 MB
- SHA256:
- e41bc51a72fb14da53299d6081da188429865f86727061477f4b0177d6da5174
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