File size: 1,354 Bytes
a175f66 d163799 cc4f13b d163799 cc4f13b |
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 |
---
datasets:
- imomayiz/morocco-img
library_name: diffusers
tags:
- art
---
# SDXL LoRA DreamBooth - imomayiz/moroccan_sdxl_lora
<Gallery />
## Model description
### These are LoRA weights of sdxl-base-1.0 finetuned on modern moroccan cities images.
The weights were trained using [DreamBooth](https://dreambooth.github.io/).
VAE used for training: madebyollin/sdxl-vae-fp16-fix.
## Trigger words
You should use "moroccan city" to trigger the image generation.
## Download model
Weights for this model are available [here](imomayiz/moroccan_sdxl_lora/tree/main).
## Dataset
The training images can be found [here](https://huggingface.co/datasets/imomayiz/morocco-img/tree/main/data/cities).
## How to use the model
```python
import torch
from diffusers import DiffusionPipeline, AutoencoderKL
repo_id = "imomayiz/moroccan_sdxl_lora"
# load lora weights and pipeline
vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
pipe = DiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
vae=vae,
torch_dtype=torch.float16,
variant="fp16",
use_safetensors=True
)
pipe.load_lora_weights(repo_id)
_ = pipe.to("cuda")
prompt = "a photo of a modern moroccan city"
# generate the image
image = pipe(prompt=prompt, num_inference_steps=20).images[0]
image
```
|