
For more info on data collection and the preprocessing algorithm, please see [Fast Anime PromptGen](https://huggingface.co/FredZhang7/anime-anything-promptgen-v2).


## 80K unique prompts
- `safebooru_clean`: Cleaned prompts with upscore ≥ 8 from the Safebooru API

---

For disclaimers about the Danbooru data, please see [Danbooru Tag Generator](https://huggingface.co/FredZhang7/danbooru-tag-generator).

## 100K unique prompts (each)
- `danbooru_raw`: Raw prompts with upscore ≥ 3 from Danbooru API
- `danbooru_clean`: Cleaned prompts with upscore ≥ 3 from Danbooru API

---

## Python

Download and save the dataset to anime_prompts.csv locally.

```bash
pip install datasets
```
```python
import csv
import datasets

dataset = datasets.load_dataset("FredZhang7/anime-prompts-180K")

train = dataset["train"]
safebooru_clean = train["safebooru_clean"]
danbooru_clean = train["danbooru_clean"]
danbooru_raw = train["danbooru_raw"]

with open("anime_prompts.csv", "w") as f:
    writer = csv.writer(f)
    writer.writerow(["safebooru_clean", "danbooru_clean", "danbooru_raw"])
    for i in range(len(safebooru_clean)):
        writer.writerow([safebooru_clean[i], danbooru_clean[i], danbooru_raw[i]])
```
task_categories:text-generation size_categories:100K<n<1M language:en license:creativeml-openrail-m region:us
{"language": ["en"], "license": "creativeml-openrail-m", "size_categories": ["100K<n<1M"], "task_categories": ["text-generation"], "viewer": false}
TAGS
#task_categories-text-generation #size_categories-100K<n<1M #language-English #license-creativeml-openrail-m #region-us 


For more info on data collection and the preprocessing algorithm, please see Fast Anime PromptGen.


## 80K unique prompts
- 'safebooru_clean': Cleaned prompts with upscore ≥ 8 from the Safebooru API

---

For disclaimers about the Danbooru data, please see Danbooru Tag Generator.

## 100K unique prompts (each)
- 'danbooru_raw': Raw prompts with upscore ≥ 3 from Danbooru API
- 'danbooru_clean': Cleaned prompts with upscore ≥ 3 from Danbooru API

---

## Python

Download and save the dataset to anime_prompts.csv locally.



## 80K unique prompts
- 'safebooru_clean': Cleaned prompts with upscore ≥ 8 from the Safebooru API

---

For disclaimers about the Danbooru data, please see Danbooru Tag Generator. ## 100K unique prompts (each)
- 'danbooru_raw': Raw prompts with upscore ≥ 3 from Danbooru API
- 'danbooru_clean': Cleaned prompts with upscore ≥ 3 from Danbooru API

--- ## Python

Download and save the dataset to anime_prompts.csv locally.
TAGS
#task_categories-text-generation #size_categories-100K<n<1M #language-English #license-creativeml-openrail-m #region-us 
 ## 80K unique prompts
- 'safebooru_clean': Cleaned prompts with upscore ≥ 8 from the Safebooru API

---

For disclaimers about the Danbooru data, please see Danbooru Tag Generator. ## 100K unique prompts (each)
- 'danbooru_raw': Raw prompts with upscore ≥ 3 from Danbooru API
- 'danbooru_clean': Cleaned prompts with upscore ≥ 3 from Danbooru API

--- ## Python

Download and save the dataset to anime_prompts.csv locally.
passage: TAGS
#task_categories-text-generation #size_categories-100K<n<1M #language-English #license-creativeml-openrail-m #region-us 
## 80K unique prompts
- 'safebooru_clean': Cleaned prompts with upscore ≥ 8 from the Safebooru API

---

For disclaimers about the Danbooru data, please see Danbooru Tag Generator.## 100K unique prompts (each)
- 'danbooru_raw': Raw prompts with upscore ≥ 3 from Danbooru API
- 'danbooru_clean': Cleaned prompts with upscore ≥ 3 from Danbooru API

---## Python

Download and save the dataset to anime_prompts.csv locally.