metadata

base_model: stabilityai/stable-diffusion-3-medium-diffusers
library_name: diffusers
license: other
instance_prompt: THUYTIEN
widget:
  - text: A photo of THUYTIEN in the office
    output:
      url: image_0.png
  - text: A photo of THUYTIEN in the office
    output:
      url: image_1.png
  - text: A photo of THUYTIEN in the office
    output:
      url: image_2.png
  - text: A photo of THUYTIEN in the office
    output:
      url: image_3.png
tags:
  - text-to-image
  - diffusers-training
  - diffusers
  - template:sd-lora
  - sd3
  - sd3-diffusers

SD3 DreamBooth - tuenguyen/sd3_thuy_tien

Prompt
A photo of THUYTIEN in the office

Model description

These are tuenguyen/sd3_thuy_tien DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers.

The weights were trained using DreamBooth with the SD3 diffusers trainer.

Was the text encoder fine-tuned? False.

Trigger words

You should use THUYTIEN to trigger the image generation.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('tuenguyen/sd3_thuy_tien', torch_dtype=torch.float16).to('cuda')
image = pipeline('A photo of THUYTIEN in the office').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]