Instructions to use lucataco/ReplicateFluxLoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lucataco/ReplicateFluxLoRA 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("lucataco/ReplicateFluxLoRA") prompt = "a boat in the style of TOK" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Flux Mona Lisa

- Prompt
- a boat in the style of TOK

- Prompt
- a car in the style of TOK
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
Trigger words
You should use TOK to trigger the image generation.
Training details
Watercolor style trained for 1000 steps
prompt: "a boat in the style of TOK"
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Model tree for lucataco/ReplicateFluxLoRA
Base model
black-forest-labs/FLUX.1-dev