metadata
base_model: stabilityai/stable-diffusion-3.5-medium
library_name: diffusers
license: other
instance_prompt: >-
The passion fruit has some brown spots on its skin, giving it a patchy look.
The spots are scattered around the surface and make the fruit look less fresh
than usual
widget: []
tags:
- text-to-image
- diffusers-training
- diffusers
- template:sd-lora
- sd3
- sd3-diffusers
SD3 DreamBooth - tomy600098/TunedModel_BrownSpot-ft_sd3.5_remove
Model description
These are tomy600098/TunedModel_BrownSpot-ft_sd3.5_remove DreamBooth weights for stabilityai/stable-diffusion-3.5-medium.
The weights were trained using DreamBooth with the SD3 diffusers trainer.
Was the text encoder fine-tuned? False.
Trigger words
You should use The passion fruit has some brown spots on its skin, giving it a patchy look. The spots are scattered around the surface and make the fruit look less fresh than usual to trigger the image generation.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('tomy600098/TunedModel_BrownSpot-ft_sd3.5_remove', torch_dtype=torch.float16).to('cuda')
image = pipeline('The passion fruit has some brown spots on its skin, giving it a patchy look. The spots are scattered around the surface and make the fruit look less fresh than usual').images[0]
License
Please adhere to the licensing terms as described [here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE.md).
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]