C4 (Colossal Clean Crawled Corpus)
Colossal Clean Crawled Corpus by Allen AI with 10.4B records, the core dataset used to train the T5 model.
C4 (Colossal Clean Crawled Corpus) is a large-scale cleaned web crawling dataset created by Allen AI. With over 10.4 billion records, it is the primary training data for the Google T5 model and has become one of the most influential datasets in the field of NLP. The corpus is sourced from Common Crawl and has undergone extensive filtering, deduplication, and quality control.
A large-scale high-quality web corpus, the cornerstone dataset for NLP pre-training and research
Over 10.4 billion cleaned web text records, covering a vast array of diverse content on the internet, providing ample training data for large-scale language models.
Utilizes extensive heuristic rules and model-based quality filtering pipelines to ensure that the text in the corpus has high linguistic quality and information density.
A reliable language recognition mechanism that accurately filters English content, ensuring linguistic consistency in the corpus and the effectiveness of model training.
Radical deduplication at the document and paragraph levels effectively eliminates redundant data, improving training efficiency and model quality.
Removes offensive content, boilerplate text, and low-quality content, ensuring the safety and usability of the corpus, suitable for various research scenarios.
Released under the ODC-By 1.0 open license, supporting research and commercial use, providing convenient data access for academia and industry.
From model pre-training to task evaluation, C4 plays a core role in various fields of NLP
As the foundational training data for large language models, providing massive high-quality text corpora for models like T5 and GPT
Training classifiers based on diverse web content domains, covering various text categories such as news, technology, and education
Extracting structured information from unstructured web text, supporting tasks like entity recognition and relation extraction
Creating evaluation datasets using diverse web sources to provide standardized benchmarks for comparing NLP model performance
Quickly access the C4 dataset via API, below is a Python call example
import requests
url = "https://api.acedata.cloud/datasets/c4"
headers = {
"Authorization": "Bearer YOUR_API_TOKEN",
"Content-Type": "application/json"
}
params = {
"count": 10, # Number of records to retrieve
"offset": 0 # Starting position
}
response = requests.get(url, headers=headers, params=params)
data = response.json()
# Print retrieved records
for record in data.get("results", []):
print(record["text"][:200])
print("---")
From registration to calling, you can start using the C4 dataset in just a few minutes
Register your Ace Data Cloud account at platform.acedata.cloud and quickly complete the developer identity verification.
Create API credentials in the console to obtain your exclusive API Token for subsequent dataset interface calls.
Use the API Token to call the C4 dataset interface to obtain high-quality web text data as needed and start your NLP project.
10.4 billion high-quality web text entries, open license, instant API access. Whether you are training large language models or building NLP applications, C4 is your ideal data source.