---
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- ai-toolkit
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: wphoto
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
widget:
- text: wphoto, luxury watch on marble surface, elegant background bokeh, professional
    product styling
  output:
    url: samples/1753259492171__000001500_3.jpg
- text: wphoto, rose gold timepiece with wooden background, warm ambient lighting,
    sophisticated composition
  output:
    url: samples/1753259474827__000001500_2.jpg
- text: wphoto, vintage watch collection arranged artistically, rich textured background,
    premium photography
  output:
    url: samples/1753259457442__000001500_1.jpg
- text: wphoto, single watch positioned on silk fabric, soft studio lighting, luxury
    brand photography
  output:
    url: samples/1753259440055__000001500_0.jpg
---

# watch_styling_photography

Model trained with AI Toolkit by Ostris

<Gallery />

## Trigger words

You should use `wphoto` 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](/username/watch_styling_photography/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-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('username/watch_styling_photography', weight_name='watch_styling_photography.safetensors')
image = pipeline('wphoto, luxury watch on marble surface, elegant background bokeh, professional product styling').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)