Instructions to use mikkoph/mikkoph-klein9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mikkoph/mikkoph-klein9b 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-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mikkoph/mikkoph-klein9b") prompt = "A close-up sideway portrait by mikkoph of a very young, nord european woman with long, straight, platinum blonde hair, looking off to the side with a serene expression. She is bare-shouldered, with soft, natural-looking makeup that includes a warm, peachy-orange eyeshadow and a glossy, pinkish-lip tint. Her shoulders are raised, partially hiding her neck. The lighting is soft and even, highlighting the smooth texture of her skin against a plain, neutral gray background. The overall mood is calm, elegant, and minimalist." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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