Instructions to use Solvenet/KaLoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Solvenet/KaLoRA 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("Solvenet/KaLoRA") prompt = "A portrait photo of MSK9980, a 60 year old female with mature heavyset BBW woman in her late 50s, short wavy dark brown hair with bangs, extremely massive heavy pendulous sagging breasts reaching waist level, huge rounded belly with prominent FUPA, fair skin with stretch marks and veins, thick thighs, wide hips" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
KaLoRA

- Prompt
- A portrait photo of MSK9980, a 60 year old female with mature heavyset BBW woman in her late 50s, short wavy dark brown hair with bangs, extremely massive heavy pendulous sagging breasts reaching waist level, huge rounded belly with prominent FUPA, fair skin with stretch marks and veins, thick thighs, wide hips
Model description
Trigger words
You should use SSBBW to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for Solvenet/KaLoRA
Base model
black-forest-labs/FLUX.1-dev




























