| | --- |
| | 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. --> |
| |
|
| |
|
| | # DreamBooth - DiogoF/Codenames-30000-V1 |
| |
|
| | 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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| |
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| | DreamBooth for the text encoder was enabled: False. |
| |
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| |
|
| | ## Intended uses & limitations |
| |
|
| | #### How to use |
| |
|
| | ```python |
| | # TODO: add an example code snippet for running this diffusion pipeline |
| | ``` |
| |
|
| | #### Limitations and bias |
| |
|
| | [TODO: provide examples of latent issues and potential remediations] |
| |
|
| | ## Training details |
| |
|
| | [TODO: describe the data used to train the model] |
