Instructions to use Migga/flux-scratch-lora-rk16-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Migga/flux-scratch-lora-rk16-random 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("Migga/flux-scratch-lora-rk16-random") prompt = "High contrast scratch defect on dark glass display, thin linear scratch, occasional diagonal orientation, sharp edges, isolated single defect, reflective glossy surface with subtle metallic sheen, fine texture on smooth surface, close-up industrial inspection photo, uniform lighting with faint glow, minimal dark background, minimal noise, shallow depth of field" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Ctrl+K