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
File size: 288 Bytes
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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.
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