Instructions to use Shakker-Labs/FLUX.1-dev-LoRA-Logo-Design with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shakker-Labs/FLUX.1-dev-LoRA-Logo-Design 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("Shakker-Labs/FLUX.1-dev-LoRA-Logo-Design") prompt = "logo,Minimalist,A man stands in front of a door,his shadow forming the word \"A\"," image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
FLUX.1-dev-LoRA-Logo-Design
This is a LoRA (Logo-Design) trained on FLUX.1-dev by CJim on Shakker AI.
Showcases

- Prompt
- logo,Minimalist,A man stands in front of a door,his shadow forming the word "A",

- Prompt
- logo,Minimalist,A pair of chopsticks and a bowl of rice with the word "Lee",

- Prompt
- wablogo,Minimalist,Leaf and cat,logo,
Trigger words
You should use wablogo, logo, Minimalist as trigger words. The recommended scale is 0.8 in diffusers.
Usage suggestion
Dual Combination: something and something, e.g., cat and coffee,
Font Combination: a shape plus a letter, e.g., a book with the word "M," or The fingerprint pattern consists of the letters "hp,"
Text Below Graphic: Below the graphic is the word "coffee," directly using with the word "XX" is also feasible
Inference
import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-Logo-Design", weight_name="FLUX-dev-lora-Logo-Design.safetensors")
pipe.fuse_lora(lora_scale=0.8)
pipe.to("cuda")
prompt = "logo,Minimalist,A bunch of grapes and a wine glass"
image = pipe(prompt,
num_inference_steps=24,
guidance_scale=3.5,
).images[0]
image.save(f"example.png")
Online Inference
You can also download this model at Shakker AI, where we provide an online interface to generate images.
Acknowledgements
This model is trained by our copyrighted users CJim. We release this model under permissions. The model follows flux-1-dev-non-commercial-license.
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