File size: 3,898 Bytes
ea8edae |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 |
---
base_model: stabilityai/stable-diffusion-3-medium-diffusers
library_name: diffusers
license: other
instance_prompt: a photo of sks person
widget:
- text: A photo of sks person
output:
url: image_0.png
- text: A photo of sks person
output:
url: image_1.png
- text: A photo of sks person
output:
url: image_2.png
- text: A photo of sks person
output:
url: image_3.png
- text: A photo of sks person
output:
url: image_4.png
- text: A photo of sks person
output:
url: image_5.png
- text: A photo of sks person
output:
url: image_6.png
- text: A photo of sks person
output:
url: image_7.png
- text: A photo of sks person
output:
url: image_8.png
- text: A photo of sks person
output:
url: image_9.png
- text: A photo of sks person
output:
url: image_10.png
- text: A photo of sks person
output:
url: image_11.png
- text: A photo of sks person
output:
url: image_12.png
- text: A photo of sks person
output:
url: image_13.png
- text: A photo of sks person
output:
url: image_14.png
- text: A photo of sks person
output:
url: image_15.png
- text: A photo of sks person
output:
url: image_16.png
- text: A photo of sks person
output:
url: image_17.png
- text: A photo of sks person
output:
url: image_18.png
- text: A photo of sks person
output:
url: image_19.png
tags:
- text-to-image
- diffusers-training
- diffusers
- lora
- template:sd-lora
- sd3
- sd3-diffusers
---
<!-- 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 LoRA - SidXXD/attack_test_1
<Gallery />
## Model description
These are SidXXD/attack_test_1 DreamBooth LoRA 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 LoRA for the text encoder enabled? False.
## Trigger words
You should use `a photo of sks person` to trigger the image generation.
## Download model
[Download the *.safetensors LoRA](SidXXD/attack_test_1/tree/main) in the Files & versions tab.
## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
```py
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('SidXXD/attack_test_1', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('A photo of sks person').images[0]
```
### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
- **LoRA**: download **[`diffusers_lora_weights.safetensors` here 💾](/SidXXD/attack_test_1/blob/main/diffusers_lora_weights.safetensors)**.
- 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](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
## 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
```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] |