base_model: stabilityai/stable-diffusion-3-medium-diffusers
library_name: diffusers
license: other
instance_prompt: >-
A photo of buffered bicycle lanes displaying a flush-surface buffer between
the bicycle lane and vehicular traffic. The buffer is a minimum of 18 inches
wide, with a preferred width of 3 feet. A 4-inch solid white line separates
vehicular traffic from the buffer, and another 4-inch solid white line marks
the boundary between the bicycle lane and the buffer. The buffer is detailed
with hatched 4-inch solid white chevrons spaced every 15 feet.
widget: []
tags:
- text-to-image
- diffusers-training
- diffusers
- lora
- template:sd-lora
- sd3
- sd3-diffusers
SD3 DreamBooth LoRA - SteveWCG/trained-sd3_buffered
Model description
These are SteveWCG/trained-sd3_buffered 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? True.
Trigger words
You should use A photo of buffered bicycle lanes displaying a flush-surface buffer between the bicycle lane and vehicular traffic. The buffer is a minimum of 18 inches wide, with a preferred width of 3 feet. A 4-inch solid white line separates vehicular traffic from the buffer, and another 4-inch solid white line marks the boundary between the bicycle lane and the buffer. The buffer is detailed with hatched 4-inch solid white chevrons spaced every 15 feet.
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('SteveWCG/trained-sd3_buffered', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('A photo of buffered bicycle lanes displaying a flush-surface buffer between the bicycle lane and vehicular traffic. The buffer is a minimum of 18 inches wide, with a preferred width of 3 feet. A 4-inch solid white line separates vehicular traffic from the buffer, and another 4-inch solid white line marks the boundary between the bicycle lane and the buffer. The buffer is detailed with hatched 4-inch solid white chevrons spaced every 15 feet.').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]