Instructions to use JohanP/MoebiusStyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JohanP/MoebiusStyle 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("JohanP/MoebiusStyle") prompt = "MBSSTL" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| license: apache-2.0 | |
| language: | |
| - en | |
| tags: | |
| - flux | |
| - diffusers | |
| - lora | |
| base_model: black-forest-labs/FLUX.1-dev | |
| pipeline_tag: text-to-image | |
| instance_prompt: MBSSTL | |
| # Moebius Lora | |
| Trained on local with FluxGym | |
| ## Trigger words | |
| You should use `MBSSTL` to trigger the image generation. | |