README.md

---
base_model: stabilityai/stable-diffusion-xl-base-1.0
library_name: diffusers
license: creativeml-openrail-m
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- text-to-image
- diffusers
- diffusers-training
- lora
inference: true
widget:
- text: monet,  a landscape of a snowy mountain region big clouds
  output:
    url: images/example_ul824c994.png
- text: >-
    monet, majestic cliffs overlooking a serene ocean, with dramatic rock
    formations bathed in soft light. The cliffs are painted in shades of green,
    ochre, and brown, contrasting with the smooth, flowing waves below,
    capturing the raw, natural beauty of the landscape
  output:
    url: images/example_kuktgiadt.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. -->


# LoRA text2image fine-tuning - SedatAl/sd-model-finetuned-lora

These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the Aedancodes/monet_dataset dataset. You can find some example images in the following. 

![img_0](./image_0.png)


LoRA for the text encoder was enabled: False.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.


## 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]