Instructions to use mikkoph/mikkoph-klein4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mikkoph/mikkoph-klein4b 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.2-klein-4B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mikkoph/mikkoph-klein4b") prompt = "by mikkoph" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Michele Balistreri's Photography Style
Model description
This LoRA is designed to replicate the photography style of mikkoph (which happens to be me). It focuses on emulating the makeup, lighting techniques, and post-processing effects that I use in my work. The model was trained using images from my portfolio, which I own and hold all rights to.
This LoRA is intended mostly for myself, but also for users interested in generating images in a style similar to my photography, offering a creative tool for experimentation and inspiration.
You can view my photography work at my website: https://michelebalistreri.photo to get a better idea of what to expect.
The trigger phrase is "by mikkoph" but it is not really needed. Using "studio shot" seems to be helpful. I suggest using a weight around 1~1.5.
Side-by-side comparison
| With LoRA | No LoRA |
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Download model
Download them in the Files & versions tab.
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Model tree for mikkoph/mikkoph-klein4b
Base model
black-forest-labs/FLUX.2-klein-4B






