README.md

---
base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
library_name: diffusers
license: creativeml-openrail-m
inference: true
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- diffusers-training
- lora
datasets:
- gigant/oldbookillustrations
pipeline_tag: text-to-image
---

<!-- 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. -->


# LoRA text2image fine-tuning - Oedon42/oldpainter-lora
These are LoRA adaption weights for stable-diffusion-v1-5/stable-diffusion-v1-5. The weights were fine-tuned on the gigant/oldbookillustrations dataset. You can find some example images in the following. 




## Intended uses & limitations

#### How to use

```python
from diffusers import DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
pipe.load_lora_weights("Oedon42/oldpainter-lora")

prompt = "1800s, 19th century, antiquity, black & white, Croatia, Europe, ruins"
image = pipe(prompt).images[0]
```

## Model Preview

Here are some preview results of the model:

<div style="display: flex; flex-wrap: wrap;">
  <div style="flex: 50%; padding: 1px;">
    <img src="./image_0.png" alt="Preview 1" style="width: 90%;"/>
  </div>
  <div style="flex: 50%; padding: 1px;">
    <img src="./image_1.png" alt="Preview 2" style="width: 90%;"/>
  </div>
  <div style="flex: 50%; padding: 1px;">
    <img src="./image_2.png" alt="Preview 3" style="width: 90%;"/>
  </div>
  <div style="flex: 50%; padding: 1px;">
    <img src="./image_3.png" alt="Preview 4" style="width: 90%;"/>
  </div>
</div>

## Training details

[TODO: describe the data used to train the model]