output_dir / README.md
bhomik7's picture
End of training
cc3db0a verified
metadata
base_model: stabilityai/stable-diffusion-3.5-medium
library_name: diffusers
license: other
instance_prompt: A beautiful UI for music app
widget:
  - text: An elegant UI for an eccomerce website
    output:
      url: image_0.png
tags:
  - text-to-image
  - diffusers-training
  - diffusers
  - lora
  - template:sd-lora
  - sd3
  - sd3-diffusers

SD3 DreamBooth LoRA - bhomik7/output_dir

Prompt
An elegant UI for an eccomerce website

Model description

These are bhomik7/output_dir DreamBooth LoRA weights for stabilityai/stable-diffusion-3.5-medium.

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 beautiful UI for music app 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-3.5-medium, torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('bhomik7/output_dir', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('An elegant UI for an eccomerce website').images[0]

Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke

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]