Instructions to use imagepipeline/Flux_Realism_Super_Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use imagepipeline/Flux_Realism_Super_Lora 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("imagepipeline/Flux_Realism_Super_Lora") prompt = "A detailed photograph of a woman with short brunette hair styled in a sleek bob haircut. She is wearing a spaghetti strap, form-fitting sequin dress that shimmers in the light, sipping champagne from a glass at an elegant bar. Her makeup is flawless, featuring glossy lipstick, smoky eyes, and perfect, striking features." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
A newer version of this model is available: black-forest-labs/FLUX.1-dev
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Model tree for imagepipeline/Flux_Realism_Super_Lora
Base model
black-forest-labs/FLUX.1-dev