Bingsu/laion-translated-to-en-korean-subset
laion-translated-to-en-korean-subset About dataset a subset data of laion/laion2B-multi-joined-translated-to-en and laion/laion1B-nolang-joined-translated-to-en, including only korean Lisence CC-BY-4.0 Data Structure Data Instance >>> from datasets import load_dataset >>> dataset = load_dataset("Bingsu/laion-translated-to-en-korean-subset") >>> dataset DatasetDict({ train: Dataset({ features: ['hash', 'URL'… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/laion-translated-to-en-korean-subset.
laion-translated-to-en-korean-subset
Dataset Description
- Homepage: laion-5b
- Download Size 1.40 GiB
- Generated Size 3.49 GiB
- Total Size 4.89 GiB
About dataset
a subset data of laion/laion2B-multi-joined-translated-to-en and laion/laion1B-nolang-joined-translated-to-en, including only korean
Lisence
CC-BY-4.0
Data Structure
Data Instance
>>> from datasets import load_dataset
>>> dataset = load_dataset("Bingsu/laion-translated-to-en-korean-subset")
>>> dataset
DatasetDict({
train: Dataset({
features: ['hash', 'URL', 'TEXT', 'ENG TEXT', 'WIDTH', 'HEIGHT', 'LANGUAGE', 'similarity', 'pwatermark', 'punsafe', 'AESTHETIC_SCORE'],
num_rows: 12769693
})
})>>> dataset["train"].features
{'hash': Value(dtype='int64', id=None),
'URL': Value(dtype='large_string', id=None),
'TEXT': Value(dtype='large_string', id=None),
'ENG TEXT': Value(dtype='large_string', id=None),
'WIDTH': Value(dtype='int32', id=None),
'HEIGHT': Value(dtype='int32', id=None),
'LANGUAGE': Value(dtype='large_string', id=None),
'similarity': Value(dtype='float32', id=None),
'pwatermark': Value(dtype='float32', id=None),
'punsafe': Value(dtype='float32', id=None),
'AESTHETIC_SCORE': Value(dtype='float32', id=None)}Data Size
download: 1.40 GiB<br> generated: 3.49 GiB<br> total: 4.89 GiB
Data Field
- 'hash':
int - 'URL':
string - 'TEXT':
string - 'ENG TEXT':
string, null data are dropped - 'WIDTH':
int, null data are filled with 0 - 'HEIGHT':
int, null data are filled with 0 - 'LICENSE':
string - 'LANGUAGE':
string - 'similarity':
float32, CLIP similarity score, null data are filled with 0.0 - 'pwatermark':
float32, Probability of containing a watermark, null data are filled with 0.0 - 'punsafe':
float32, Probability of nsfw image, null data are filled with 0.0 - 'AESTHETIC_SCORE':
float32, null data are filled with 0.0
Data Splits
polars
pip install polars[fsspec]import polars as pl
from huggingface_hub import hf_hub_url
url = hf_hub_url("Bingsu/laion-translated-to-en-korean-subset", filename="train.parquet", repo_type="dataset")
# url = "https://huggingface.co/datasets/Bingsu/laion-translated-to-en-korean-subset/resolve/main/train.parquet"
df = pl.read_parquet(url)pandas broke my colab session.
