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
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Download README.md from schrum2/MarioDiffusion-MLM-negative0: direct link, hf CLI and curl.
- Browser
- Download file 547 Bytes
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https://huggingface.co/schrum2/MarioDiffusion-MLM-negative0/resolve/main/README.md
- Command line
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hf download hf://schrum2/MarioDiffusion-MLM-negative0/README.md
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curl -L -o README.md https://huggingface.co/schrum2/MarioDiffusion-MLM-negative0/resolve/main/README.md
547 Bytes
| license: mit | |
| Details on the code used to produce and use this model are available at: | |
| https://github.com/schrum2/MarioDiffusion | |
| That repo has instructions to check out this model and apply it to the generation of Super Mario Bros. level scenes. | |
| There is also an interactive GUI for constructing complete levels out of model-generated scenes. | |
| This model supports negative prompts, though we recommend generating negative prompts automatically | |
| using the settings available in specific inference scripts in the GitHub repo linked above. |