---
license: mit
task_categories:
- text-generation
language:
- en
tags:
- image-generation
- diffusion
- prompts
- flux
- stable-diffusion
pretty_name: Image Diffusion Prompt Style
size_categories:
- n<1K
dataset_info:
  features:
  - name: style_name
    dtype: string
  - name: prompt_text
    dtype: string
  - name: negative_prompt
    dtype: string
  - name: tags
    list: string
  - name: compatible_models
    list: string
  splits:
  - name: train
    num_bytes: 505421
    num_examples: 750
  download_size: 178464
  dataset_size: 505421
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Image Diffusion Prompt Style

High-quality synthetic prompts for image diffusion models, optimized for **Flux**, **Z Image**, and **Qwen**.

## Dataset Structure

| Column | Type | Description |
|--------|------|-------------|
| `style_name` | string | Short descriptive name |
| `prompt_text` | string | Full prompt with quality tokens |
| `negative_prompt` | string | Artifacts to avoid |
| `tags` | list | Lowercase keywords |
| `compatible_models` | list | Target models |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("Limbicnation/Images-Diffusion-Prompt-Style", split="train")
prompt = ds[0]["prompt_text"]
```

## Aesthetic

Prompts emphasize the **Limbicnation** style:
- Cinematic lighting
- Intricate textures
- Evocative atmosphere
- Dramatic compositions

## License

MIT