metadata
base_model: stabilityai/stable-diffusion-3-medium-diffusers
library_name: diffusers
license: other
instance_prompt: >-
a photo of a young canola plant that is about 20 days old. It has five leaves
that are starting to develop
widget:
- text: >-
A photo of a young canola plant, about 20 to 29 days old with five
developing leaves. It is growing in dark, nutrient-rich soil. It is
contained within a smooth, bright blue cylindrical cup on a bright blue
background
output:
url: image_0.png
- text: >-
A photo of a young canola plant, about 20 to 29 days old with five
developing leaves. It is growing in dark, nutrient-rich soil. It is
contained within a smooth, bright blue cylindrical cup on a bright blue
background
output:
url: image_1.png
- text: >-
A photo of a young canola plant, about 20 to 29 days old with five
developing leaves. It is growing in dark, nutrient-rich soil. It is
contained within a smooth, bright blue cylindrical cup on a bright blue
background
output:
url: image_2.png
- text: >-
A photo of a young canola plant, about 20 to 29 days old with five
developing leaves. It is growing in dark, nutrient-rich soil. It is
contained within a smooth, bright blue cylindrical cup on a bright blue
background
output:
url: image_3.png
tags:
- text-to-image
- diffusers-training
- diffusers
- lora
- template:sd-lora
- sd3
- sd3-diffusers
SD3 DreamBooth LoRA - rdeinla/test-can-2

- Prompt
- A photo of a young canola plant, about 20 to 29 days old with five developing leaves. It is growing in dark, nutrient-rich soil. It is contained within a smooth, bright blue cylindrical cup on a bright blue background

- Prompt
- A photo of a young canola plant, about 20 to 29 days old with five developing leaves. It is growing in dark, nutrient-rich soil. It is contained within a smooth, bright blue cylindrical cup on a bright blue background

- Prompt
- A photo of a young canola plant, about 20 to 29 days old with five developing leaves. It is growing in dark, nutrient-rich soil. It is contained within a smooth, bright blue cylindrical cup on a bright blue background

- Prompt
- A photo of a young canola plant, about 20 to 29 days old with five developing leaves. It is growing in dark, nutrient-rich soil. It is contained within a smooth, bright blue cylindrical cup on a bright blue background
Model description
These are rdeinla/test-can-2 DreamBooth LoRA weights for stabilityai/stable-diffusion-3-medium-diffusers.
The weights were trained using DreamBooth with the SD3 diffusers trainer.
Was LoRA for the text encoder enabled? False.
Trigger words
You should use a photo of a young canola plant that is about 20 days old. It has five leaves that are starting to develop
to trigger the image generation.
Download model
Download the *.safetensors LoRA in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained(stabilityai/stable-diffusion-3-medium-diffusers, torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('rdeinla/test-can-2', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('A photo of a young canola plant, about 20 to 29 days old with five developing leaves. It is growing in dark, nutrient-rich soil. It is contained within a smooth, bright blue cylindrical cup on a bright blue background').images[0]
Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
- LoRA: download
diffusers_lora_weights.safetensors
here 💾.- Rename it and place it on your
models/Lora
folder. - On AUTOMATIC1111, load the LoRA by adding
<lora:your_new_name:1>
to your prompt. On ComfyUI just load it as a regular LoRA.
- Rename it and place it on your
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
License
Please adhere to the licensing terms as described here.
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]