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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

preview

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
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Finetuned from

Dataset used to train iamkaikai/amazing-logos