| --- |
| license: creativeml-openrail-m |
| library_name: diffusers |
| tags: |
| - text-to-image |
| - dreambooth |
| - diffusers-training |
| - stable-diffusion |
| - stable-diffusion-diffusers |
| base_model: CompVis/stable-diffusion-v1-4 |
| inference: true |
| instance_prompt: the <codenames> style |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the training script had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
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| # DreamBooth - DiogoF/Codenames-10000-Text-Encoding-V1 |
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| This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on the <codenames> style using [DreamBooth](https://dreambooth.github.io/). |
| You can find some example images in the following. |
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| DreamBooth for the text encoder was enabled: True. |
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| ## Intended uses & limitations |
|
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| #### How to use |
|
|
| ```python |
| # TODO: add an example code snippet for running this diffusion pipeline |
| ``` |
|
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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] |
