Instructions to use schrum2/MarioDiffusion-MLM-absence0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MLM-absence0 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-absence0", 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:
- 976d28924693653d6bab84297b27e2deab8b9c2830596765872a958fd74d6ea7
- Size of remote file:
- 2.17 MB
- SHA256:
- 542f53373f899ee7b9b07507a9d76466ec8d87039df855e26037e8d0c6c95a8d
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