---
language:
- en
license: apache-2.0
multilinguality:
- monolingual
source_datasets:
- bartman081523/stable-diffusion-discord-prompts
- succinctly/midjourney-prompts
- Gustavosta/Stable-Diffusion-Prompts
pretty_name: multi text2image prompts a dataset collection
tags:
- text generation
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
- config_name: original
  data_files:
  - split: train
    path: original/train-*
  - split: test
    path: original/test-*
dataset_info:
- config_name: default
  features:
  - name: text
    dtype: string
  - name: src_dataset
    dtype: string
  splits:
  - name: train
    num_bytes: 262736830
    num_examples: 1677221
  - name: test
    num_bytes: 56294291
    num_examples: 292876
  download_size: 151054782
  dataset_size: 319031121
- config_name: original
  features:
  - name: text
    dtype: string
  - name: src_dataset
    dtype: string
  splits:
  - name: train
    num_bytes: 741427383
    num_examples: 3551734
  - name: test
    num_bytes: 83615440
    num_examples: 399393
  download_size: 402186258
  dataset_size: 825042823
task_categories:
- text-generation
- feature-extraction
---


# text2image multi-prompt(s): a dataset collection

- collection of several text2image prompt datasets
- data was cleaned/normalized with the goal of removing "model specific APIs" like the "--ar" for Midjourney and so on
- data de-duplicated on a basic level: exactly duplicate prompts were dropped (_after cleaning and normalization_)

## updates

- Oct 2023: the `default` config has been updated with better deduplication. It was deduplicated with minhash (_params: n-gram size set to 3, deduplication threshold at 0.6, hash function chosen as xxh3 with 32-bit hash bits, and 128 permutations with a batch size of 10,000._) which drops 2+ million rows.
  - original version is still available under `config_name="original"`

## contents



default:

```
DatasetDict({
    train: Dataset({
        features: ['text', 'src_dataset'],
        num_rows: 1677221
    })
    test: Dataset({
        features: ['text', 'src_dataset'],
        num_rows: 292876
    })
})
```

For `original` config:
```
DatasetDict({
    train: Dataset({
        features: ['text', 'src_dataset'],
        num_rows: 3551734
    })
    test: Dataset({
        features: ['text', 'src_dataset'],
        num_rows: 399393
    })
})
```

_NOTE: as the other two datasets did not have a `validation` split, the validation split of `succinctly/midjourney-prompts` was merged into `train`._