Instructions to use schrum2/MarioDiffusion-MiniLM-multiple-regular0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MiniLM-multiple-regular0 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-MiniLM-multiple-regular0", 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:
- dfe6092a8cba4e930da66c7e96efef8a6d8b6ebaf049242b4c3e528625c1b01e
- Size of remote file:
- 401 MB
- SHA256:
- 7f44cd4891b94acdbc3344ea1dbc7876917f6528d90ec38e3761e14f852d99e8
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