Instructions to use schrum2/MarioDiffusion-MiniLM-single-negative0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MiniLM-single-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-single-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
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 makes use of https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1 as a text embedding model for use with diffusion to generate Mario levels. It also makes use of negative guidance during diffusion training.
To see a model using sentence-transformers/multi-qa-MiniLM-L6-cos-v1 without negative guidance, see https://huggingface.co/schrum2/MarioDiffusion-MiniLM-single-regular0. To see a model that uses negative guidance with a simple token-based transformer model for text embedding, see https://huggingface.co/schrum2/MarioDiffusion-MLM-negative0.
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