| | --- |
| | 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 makes use of https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5 |
| | as a text embedding model for use with diffusion to generate Mario levels. |
| | It makes use of negative guidance during diffusion training, and encodes each |
| | of several phrases within each caption as a distinct text embedding. |
| | Our results indicate that it has relatively poor performance, so it is made available |
| | only to allow full scrutiny of our results. |
| |
|
| | To see a model using Alibaba-NLP/gte-large-en-v1.5 that performs better with |
| | multiple text embeddings without using negative guidance, |
| | see https://huggingface.co/schrum2/MarioDiffusion-GTE-multiple-regular0. |
| | To see a model that uses |
| | a simple token-based transformer model for text embedding |
| | and makes use of negative guidance, see https://huggingface.co/schrum2/MarioDiffusion-MLM-negative0. |
