61
stars
181
commits
4
linked in READMEs
Nov 1, 2024
updated
GlotCC-V1.0 is a document-level, general domain dataset derived from CommonCrawl, covering more than 1000 languages.
It is built using the GlotLID language identification and Ungoliant pipeline from CommonCrawl.
We release our pipeline as open-source at https://github.com/cisnlp/GlotCC.
List of Languages: See https://datasets-server.huggingface.co/splits?dataset=cis-lmu/GlotCC-V1 to get the list of splits available.
Replace bal-Arab with your specific language.
from huggingface_hub import snapshot_download
folder = snapshot_download(
"cis-lmu/glotcc-v1",
repo_type="dataset",
local_dir="./path/to/glotcc-v1/",
# Replace "v1.0/bal-Arab/*" with the path for any other language available in the dataset
allow_patterns="v1.0/bal-Arab/*"
)
For faster downloads, make sure to pip install huggingface_hub[hf_transfer] and set the environment variable HF_HUB_ENABLE_HF_TRANSFER=1.
Then you can load it with any library that supports Parquet files, such as Pandas:
import pandas as pd
# Load the dataset from a Parquet file
# Replace the file path with the path to the desired language's Parquet file
dataset = pd.read_parquet('./path/to/glotcc-v1/v1.0/bal-Arab/bal-Arab_0.parquet')
# Print the first 5 rows of the dataset
print(dataset.head())
from datasets import load_dataset
# Replace "bal-Arab" with the name of any other language available in the dataset
dataset = load_dataset("cis-lmu/glotcc-v1", name="bal-Arab", split="train")
# Print the first row of data
print(dataset[0])
from datasets import load_dataset
# Replace "bal-Arab" with the name of any other language available in the dataset
fw = load_dataset("cis-lmu/glotcc-v1", name="bal-Arab", split="train", streaming=True)
# Create an iterator from the streaming dataset
iterator = iter(fw)
# Print the next item from the iterator
print(next(iterator))
If you prefer not to use the Hugging Face datasets or hub you can download it directly. For example, to download the first file of bal-Arab:
!wget https://huggingface.co/datasets/cis-lmu/GlotCC-V1/resolve/main/v1.0/bal-Arab/bal-Arab_0.parquet
The dataset is currently heavily under audit and changes accordingly.
GlotCC data is released under the following licensing scheme: We do not own any of the text from which this data has been extracted. The data is licensed under the terms of the CommonCrawl Terms of Use. We license the actual packaging, metadata, and annotations of this data under the Creative Commons CC0 license.
If you find our data useful for your research, please cite:
@article{kargaran2024glotcc,
title = {Glot{CC}: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages},
author = {Kargaran, Amir Hossein and Yvon, Fran{\c{c}}ois and Sch{\"u}tze, Hinrich},
journal = {Advances in Neural Information Processing Systems},
year = {2024},
url = {https://arxiv.org/abs/2410.23825}
}
181 commits
61
stars
181
commits
4
linked in READMEs
Nov 1, 2024
updated
GlotCC-V1.0 is a document-level, general domain dataset derived from CommonCrawl, covering more than 1000 languages.
It is built using the GlotLID language identification and Ungoliant pipeline from CommonCrawl.
We release our pipeline as open-source at https://github.com/cisnlp/GlotCC.
List of Languages: See https://datasets-server.huggingface.co/splits?dataset=cis-lmu/GlotCC-V1 to get the list of splits available.
Replace bal-Arab with your specific language.
from huggingface_hub import snapshot_download
folder = snapshot_download(
"cis-lmu/glotcc-v1",
repo_type="dataset",
local_dir="./path/to/glotcc-v1/",
# Replace "v1.0/bal-Arab/*" with the path for any other language available in the dataset
allow_patterns="v1.0/bal-Arab/*"
)
For faster downloads, make sure to pip install huggingface_hub[hf_transfer] and set the environment variable HF_HUB_ENABLE_HF_TRANSFER=1.
Then you can load it with any library that supports Parquet files, such as Pandas:
import pandas as pd
# Load the dataset from a Parquet file
# Replace the file path with the path to the desired language's Parquet file
dataset = pd.read_parquet('./path/to/glotcc-v1/v1.0/bal-Arab/bal-Arab_0.parquet')
# Print the first 5 rows of the dataset
print(dataset.head())
from datasets import load_dataset
# Replace "bal-Arab" with the name of any other language available in the dataset
dataset = load_dataset("cis-lmu/glotcc-v1", name="bal-Arab", split="train")
# Print the first row of data
print(dataset[0])
from datasets import load_dataset
# Replace "bal-Arab" with the name of any other language available in the dataset
fw = load_dataset("cis-lmu/glotcc-v1", name="bal-Arab", split="train", streaming=True)
# Create an iterator from the streaming dataset
iterator = iter(fw)
# Print the next item from the iterator
print(next(iterator))
If you prefer not to use the Hugging Face datasets or hub you can download it directly. For example, to download the first file of bal-Arab:
!wget https://huggingface.co/datasets/cis-lmu/GlotCC-V1/resolve/main/v1.0/bal-Arab/bal-Arab_0.parquet
The dataset is currently heavily under audit and changes accordingly.
GlotCC data is released under the following licensing scheme: We do not own any of the text from which this data has been extracted. The data is licensed under the terms of the CommonCrawl Terms of Use. We license the actual packaging, metadata, and annotations of this data under the Creative Commons CC0 license.
If you find our data useful for your research, please cite:
@article{kargaran2024glotcc,
title = {Glot{CC}: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages},
author = {Kargaran, Amir Hossein and Yvon, Fran{\c{c}}ois and Sch{\"u}tze, Hinrich},
journal = {Advances in Neural Information Processing Systems},
year = {2024},
url = {https://arxiv.org/abs/2410.23825}
}
181 commits