metadata

base_model: stabilityai/stable-diffusion-3-medium-diffusers
library_name: diffusers
license: openrail++
tags:
  - text-to-image
  - diffusers-training
  - diffusers
  - sd3
  - sd3-diffusers
  - template:sd-lora
instance_prompt: niul, colorful object, engraved with NiUl
widget:
  - text: niul, colorful object, engraved with NiUl
    output:
      url: image_0.png
  - text: niul, colorful object, engraved with NiUl
    output:
      url: image_1.png
  - text: niul, colorful object, engraved with NiUl
    output:
      url: image_2.png
  - text: niul, colorful object, engraved with NiUl
    output:
      url: image_3.png

SD3 DreamBooth - hjvision/models

Prompt
niul, colorful object, engraved with NiUl

Model description

These are hjvision/models 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 niul, colorful object, engraved with NiUl to trigger the image generation.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('hjvision/models', torch_dtype=torch.float16).to('cuda')
image = pipeline('niul, colorful object, engraved with NiUl').images[0]

License

Please adhere to the licensing terms as described [here](https://huggingface.co./stabilityai/stable-diffusion-3-medium/blob/main/LICENSE).

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]