Instructions to use Jonjew/BrookeBurke with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/BrookeBurke 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("Jonjew/BrookeBurke") prompt = "A professional photograph of a young woman Brooke_Burke wearing a dark green cableknit sweater in a cafe, holding a latte, brunette hair, detailed skin, bokeh, female focus, SFW, smiling<lora:Brooke_Burke:1>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Brooke Burke

- Prompt
- A professional photograph of a young woman Brooke_Burke wearing a dark green cableknit sweater in a cafe, holding a latte, brunette hair, detailed skin, bokeh, female focus, SFW, smiling<lora:Brooke_Burke:1>
- Negative Prompt
- <lora:Brooke_Burke:1>
Model description
FROM https://civitai.com/models/1077209/brooke-burke?modelVersionId=1209288
Trigger Brooke_Burke
Trigger words
You should use Brooke_Burke to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for Jonjew/BrookeBurke
Base model
black-forest-labs/FLUX.1-dev