--- base_model: stabilityai/stable-diffusion-3-medium-diffusers library_name: diffusers license: openrail++ tags: - text-to-image - diffusers-training - diffusers - sd3 - sd3-diffusers - template:sd-lora instance_prompt: a photo of m1nd3xpand3r person wearing a colorful mask with an eye on the forehead, in a green park with city buildings in the background widget: - text: a photo of m1nd3xpand3r person wearing a colorful mask with an eye on the forehead, standing in a city park with a unique background output: url: image_0.png - text: a photo of m1nd3xpand3r person wearing a colorful mask with an eye on the forehead, standing in a city park with a unique background output: url: image_1.png - text: a photo of m1nd3xpand3r person wearing a colorful mask with an eye on the forehead, standing in a city park with a unique background output: url: image_2.png - text: a photo of m1nd3xpand3r person wearing a colorful mask with an eye on the forehead, standing in a city park with a unique background output: url: image_3.png --- # SD3 DreamBooth LoRA - TheMindExpansionNetwork/m1nd3xpand3r-sd3-lora ## Model description These are TheMindExpansionNetwork/m1nd3xpand3r-sd3-lora DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers. The weights were trained using [DreamBooth](https://dreambooth.github.io/). ## Trigger words You should use a photo of m1nd3xpand3r person wearing a colorful mask with an eye on the forehead, in a green park with city buildings in the background to trigger the image generation. ## Download model [Download](TheMindExpansionNetwork/m1nd3xpand3r-sd3-lora/tree/main) them in the Files & versions tab. ## License Please adhere to the licensing terms as described `[here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE)`. ## 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]