metadata
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
- Prompt
- wphoto, luxury watch on marble surface, elegant background bokeh, professional product styling
- Prompt
- wphoto, rose gold timepiece with wooden background, warm ambient lighting, sophisticated composition
- Prompt
- wphoto, vintage watch collection arranged artistically, rich textured background, premium photography
- Prompt
- wphoto, single watch positioned on silk fabric, soft studio lighting, luxury brand photography
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 them in the Files & versions tab.
Use it with the 🧨 diffusers library
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