Instructions to use Omnico/Flux.1_Schnell-Dev_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-Dev_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-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Omnico/Flux.1_Schnell-Dev_diff_loras") prompt = "The palette is dominated by dark tones. The texture is pronounced, with brushstrokes and traces of paint visible, imitating the process of painting using multi-layered tones. The composition is centered around the figures, and the background flows smoothly in color and tone. The style is abstract, almost sculptural. The style is abstract, almost sculptural. Free, gestural brushstrokes create a sense of movement and action. The muted color palette includes subtle variations in tone. The sense of depth is achieved through different densities of brushstrokes. The light source is diffused, giving the image a slightly cool and mysterious shade. The style of painting is reminiscent of abstract realism and expressionism." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Ctrl+K
- images
- 2.31 kB
- 11.1 kB
- 1.11 GB xet
- 2.21 GB xet
- 3.32 GB xet
- 553 MB xet
- 1.11 GB xet
- 2.21 GB xet
- 3.32 GB xet
- 553 MB xet
- 1.11 GB xet
- 2.21 GB xet
- 3.32 GB xet
- 553 MB xet
- 1.11 GB xet
- 2.21 GB xet
- 3.32 GB xet
- 553 MB xet
- 1.11 GB xet
- 2.21 GB xet
- 3.32 GB xet
- 553 MB xet
- 1.11 GB xet
- 2.21 GB xet
- 3.32 GB xet
- 553 MB xet
- 1.11 GB xet
- 2.21 GB xet
- 3.32 GB xet
- 553 MB xet
- 1.11 GB xet
- 2.21 GB xet
- 3.32 GB xet
- 553 MB xet