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--- |
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base_model: CompVis/stable-diffusion-v1-4 |
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library_name: diffusers |
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license: creativeml-openrail-m |
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tags: |
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- text-to-image |
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- dreambooth |
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- diffusers-training |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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inference: true |
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instance_prompt: any two tiles of blue color are connected through a path with non-black |
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tiles, each blue tile is adjacent to at least one black tile, each black tile is |
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adjacent to at least two blue tiles. |
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--- |
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<!-- This model card has been generated automatically according to the information the training script had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# DreamBooth - bhuv1-c/db-valid-warehouse-try6 |
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This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on any two tiles of blue color are connected through a path with non-black tiles, each blue tile is adjacent to at least one black tile, each black tile is adjacent to at least two blue tiles. using [DreamBooth](https://dreambooth.github.io/). |
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You can find some example images in the following. |
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DreamBooth for the text encoder was enabled: False. |
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## Intended uses & limitations |
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#### How to use |
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```python |
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# TODO: add an example code snippet for running this diffusion pipeline |
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``` |
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#### Limitations and bias |
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[TODO: provide examples of latent issues and potential remediations] |
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## Training details |
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[TODO: describe the data used to train the model] |
