Instructions to use sangram2921/Brooke_Monk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sangram2921/Brooke_Monk 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("sangram2921/Brooke_Monk") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Brooke Monk

- Prompt
- -
- Negative Prompt
- -

- Prompt
- -
- Negative Prompt
- -
Model description
Flux [dev] Lora of Brooke Monk From https://civitai.com/models/1191954/brooke-monk-flux-or-social-media-influencer-instagram-model
Strength - 1.2-1.3
Trigger words
You should use brooke_mk to trigger the image generation.
You should use Brooke Monk 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 sangram2921/Brooke_Monk
Base model
black-forest-labs/FLUX.1-dev