---
license: openrail++
library_name: diffusers
tags:
- text-to-image
- diffusers
- diffusers-training
- lora
- template:sd-lorastable-diffusion
- stable-diffusion-diffusers
base_model: runwayml/stable-diffusion-v1-5
inference: true
instance_prompt: A mushroom in [V] style
widget:
- text: ' '
  output:
    url: image_0.png
- text: ' '
  output:
    url: image_1.png
- text: ' '
  output:
    url: image_2.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. -->


# SD1.5 LoRA DreamBooth - abby101/test

<Gallery />

## Model description

### These are abby101/test LoRA adaption weights for runwayml/stable-diffusion-v1-5.

## Download model

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

- **LoRA**: download **[`..safetensors` here 💾](/abby101/test/blob/main/..safetensors)**.
    - Place it on your `models/Lora` folder.
    - On AUTOMATIC1111, load the LoRA by adding `<lora:.:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).


## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('abby101/test', weight_name='pytorch_lora_weights.safetensors')

image = pipeline('A mushroom in [V] style').images[0]
```

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)

## Trigger words

You should use A mushroom in [V] style to trigger the image generation.

## Details
All [Files & versions](/abby101/test/tree/main).

The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sd15_advanced.py).

LoRA for the text encoder was enabled. False.

Pivotal tuning was enabled: False.

Special VAE used for training: None.



## 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]