Instructions to use kadirnar/vton_mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kadirnar/vton_mini with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kadirnar/vton_mini", dtype=torch.bfloat16, device_map="cuda") prompt = "model is wearing" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
SD3 DreamBooth LoRA - kadirnar/vton_mini

- Prompt
- model is wearing

- Prompt
- model is wearing

- Prompt
- model is wearing

- Prompt
- model is wearing
Model description
These are kadirnar/vton_mini DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers.
The weights were trained using DreamBooth.
Trigger words
You should use model is wearing 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]
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