Instructions to use chrismasch/whtsnk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chrismasch/whtsnk with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("chrismasch/whtsnk") prompt = "A photo of a pair of whtsnk with a low-top design in the style of whtsnk. The whtsnk feature a clean, minimalist look with perforations on the toe box for breathability and white laces. The sole is white, with a textured pattern for traction." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
whtsnk

- Prompt
- A photo of a pair of whtsnk with a low-top design in the style of whtsnk. The whtsnk feature a clean, minimalist look with perforations on the toe box for breathability and white laces. The sole is white, with a textured pattern for traction.
Model description
LoRA for FLUX.1-dev trained on 101 high res images of white sneakers.
Trigger words
You should use whtsnk to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for chrismasch/whtsnk
Base model
black-forest-labs/FLUX.1-dev