Instructions to use Omnico/Flux.1_Schnell-Schnell_diff_loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Omnico/Flux.1_Schnell-Schnell_diff_loras 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-schnell", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Omnico/Flux.1_Schnell-Schnell_diff_loras") prompt = "(Soft Lighting Photography by Mimoza Veliu and Mario Giacomelli:1.2), Photo of TWbabeXL01, NSFW, neon dress, neon outlines, 1 girl, nude, (wind:1.3), long hair, A futuristic woman, aurora, her silhouette defined by vibrant neon lines, stands amidst a swirling storm. Her eyes, filled with intense emotion, gaze towards a distant horizon. The scene captures a poignant moment of farewell, framed in a cinematic style. The atmosphere is charged with the electric buzz of the future, yet tinged with the melancholy of memories fading into the past." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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