README.md

---
base_model: black-forest-labs/FLUX.1-schnell
license: apache-2.0
tags:
- autotrain
- spacerunner
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
widget:
- text: a bride and groom standing next to each other in front of a white background,
    both of them smiling and holding flower bouquets in their hands. The bride is
    wearing a white dress and the groom is holding a bouquet of flowers w3yg
  output:
    url: samples/1726237587125__000001000_0.jpg
- text: two lovely couple standing in church and seeing each other, earing in nice
    dress w3yg
  output:
    url: samples/1726237604671__000001000_1.jpg
instance_prompt: w3yg
---

# wedding-yg
Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
<Gallery />

## Trigger words

You should use `w3yg` to trigger the image generation.

## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.

Weights for this model are available in Safetensors format.

[Download](/cctuan/wedding-yg/tree/main) them in the Files & versions tab.

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

```py
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-schnell', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cctuan/wedding-yg', weight_name='wedding-yg')
image = pipeline('a bride and groom standing next to each other in front of a white background, both of them smiling and holding flower bouquets in their hands. The bride is wearing a white dress and the groom is holding a bouquet of flowers w3yg').images[0]
image.save("my_image.png")
```

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)