metadata
license: openrail++
library_name: diffusers
tags:
- text-to-image
- diffusers-training
- diffusers
- sd3
- sd3-diffusers
- template:sd-lora
base_model: stabilityai/stable-diffusion-3-medium-diffusers
instance_prompt: a photo of Medium Thick knit pullover
widget:
- text: A photo of Medium Thick knit pullover on a mannequin or torso
output:
url: image_0.png
- text: A photo of Medium Thick knit pullover on a mannequin or torso
output:
url: image_1.png
- text: A photo of Medium Thick knit pullover on a mannequin or torso
output:
url: image_2.png
- text: A photo of Medium Thick knit pullover on a mannequin or torso
output:
url: image_3.png
SD3 DreamBooth LoRA - TE2G/MediumThick

- Prompt
- A photo of Medium Thick knit pullover on a mannequin or torso

- Prompt
- A photo of Medium Thick knit pullover on a mannequin or torso

- Prompt
- A photo of Medium Thick knit pullover on a mannequin or torso

- Prompt
- A photo of Medium Thick knit pullover on a mannequin or torso
Model description
These are TE2G/MediumThick DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers.
The weights were trained using DreamBooth.
Trigger words
You should use a photo of Medium Thick knit pullover to trigger the image generation.
Download model
Download 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
# 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]