Text-to-image finetuning - iamkaikai/amazing-logos
This pipeline was finetuned from runwayml/stable-diffusion-v1-5 on the iamkaikai/amazing_logos_v2 dataset.
Training info
These are the key hyperparameters used during training:
- Dataset size: 10k
- Epochs: 20
- Learning rate: 1e-07
- Batch size: 1
- Gradient accumulation steps: 1
- Image resolution: 512
- Mixed-precision: fp16
Prompt Format
The prompt format is as follows:
{template keywords} + [company name] + [concept & country] + {template keywords}
For example:
Simple elegant logo for **[Google]**, **[G circle United states]**, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white
The [concept & country] section can include words such as:
- lines
- circles
- triangles
- dot
- crosses
- waves
- square
- letters (A-Z)
- 3D
- Angled
- Arrows
- cube
- Diamond
- Hexagon
- Loops
- outline
- ovals
- rectangle
- reflection
- rings
- round
- semicircle
- spiral
- woven
- stars
Here are some examples of prompts:
- Simple elegant logo for Digital Art, D A circle, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white
- Simple elegant logo for 3M Technology Products, 3 M square United states, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white
- Simple elegant logo for 38Energy, lines drop fire flame water, successful vibe, minimalist, thought provoking, abstract, recognizable, relatable, sharp, vector art, even edges, black and white
- Downloads last month
- 3
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for iamkaikai/amazing-logos
Base model
runwayml/stable-diffusion-v1-5