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updated readme and metadata

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  1. README.md +41 -1
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@@ -28,7 +28,47 @@ configs:
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  data_files:
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  - split: train
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  path: data/train-*
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for "stable-diffusion-prompts-stats-full-uncensored"
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- [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  data_files:
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  - split: train
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  path: data/train-*
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+ license: mit
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+ task_categories:
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+ - image-to-image
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+ - text-classification
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+ - text-to-image
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+ language:
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+ - en
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+ tags:
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+ - uncensored
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+ - nsfw
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+ - stable diffusion
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+ - art
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+ - not-for-all-audiences
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+ pretty_name: stable diffusion prompts
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+ size_categories:
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+ - 1M<n<10M
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  ---
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  # Dataset Card for "stable-diffusion-prompts-stats-full-uncensored"
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+ # Dataset Card for "stable-diffusion-prompts-uncensored"
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+
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+ ## Not SAFE for public - Definately Unfiltered with URL links
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+
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+ This dataset comes from prompts shared from images' metadata on Civitai. Not for the faint of heart.
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+ Thanks to Civitai.com for all the models, building a playground, allowing fine tuning of models, and generally being a good influence on model building and generation.
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+
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+ The purpose of this dataset is to allow for analysis of prompts and feature analysis in prompts and negative prompts.
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+
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+ This could be for:
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+ - semantic evaluation (see stats column)
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+ - prompt quality
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+ - effective prompting
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+ - prompt alignment or misalignment
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+ - statistical research on prompts and categories
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+ - popularity of image generation approaches
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+ - mimimalism prompts with certain models
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+ - matching generated prompts to images for LLAVA purposes
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+ - mimimizing prompts for better context usage
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+ - social research on interest level and creative approaches
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+ - modeling based on prompts for automating prompt generation strategy
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+ - modeling of categorical interest and similarity
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+ - modeling of evolution of prompts based on model versioning
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+
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+ A seperate upload includes only prompts, negative prompts, and model name for brevity, squeamishness, and research purposes.