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---
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
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SD3 DreamBooth - hjvision/models
<Gallery />
## Model description
These are hjvision/models DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers.
The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
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](https://github.com/huggingface/diffusers)
```py
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
```python
# 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] |