Instructions to use schrum2/MarioDiffusion-MiniLM-multiple-negative0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MiniLM-multiple-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-MiniLM-multiple-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:
- 1cb88d7d48bf884b1d950f03a76d76115d65636d6f6f0f506099351a25ddfa95
- Size of remote file:
- 401 MB
- SHA256:
- 8f1a54688293fdf110d5666b428ff4a28f8534a0a67a39274eae0a09c870491c
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