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---
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- text-to-image
- diffusers
- lora
- template:sd-lora
widget:
- text: in the style of TOK
output:
url: 000.png
- text: Face closeup, Beautiful young woman
output:
url: 001.png
- text: in the style of TOK
output:
url: 002.png
- text: beautiful woman with red eyes
output:
url: 003.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: in the style of TOK
license: openrail++
datasets:
- Chan-Y/Fish
---
# Chan-Y/FantasticStyle-LoRA
<Gallery />
## Model description
### These are besni LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
## Download model
### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
- **LoRA**: download **[`besni.safetensors` here 💾](/besni/blob/main/besni.safetensors)**.
- Place it on your `models/Lora` folder.
- On AUTOMATIC1111, load the LoRA by adding `<lora:besni: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('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('Chan-Y/FantasticStyle-LoRA', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('in the style of TOK', num_inference_steps=50).images[0]
image
```
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 in the style of TOK to trigger the image generation.
## Details
All [Files & versions](/besni/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_sdxl_advanced.py).
LoRA for the text encoder was enabled. True.
Pivotal tuning was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix. |