Datasets:
File size: 1,997 Bytes
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language:
- it
license: cc-by-4.0
task_categories:
- text-generation
tags:
- italian
- modotai
- pretraining
- corpus
size_categories:
- 1M<n<10M
---
# Italian-Common-Corpus
The Italian dataset with the highest density of useful information per token. Built by [ModotAI](https://things-ai.org) for training Italian language models.
## Subsets
| Subset | File | Documents | Words | Description |
|--------|------|-----------|-------|-------------|
| **Web Crawl** | `icc-web.parquet` | ~27K | ~17M | Italian sources: news, tech, science, culture, law, food, sport |
| **Wikipedia IT** | `wiki-it-clean.parquet` | ~1.35M | ~698M | Cleaned Italian Wikipedia — removed Notes, Bibliography, Voci correlate, stub articles |
**Total: 1,377,369 documents, 715,313,213 words (~929M tokens)**
## Usage
```python
from datasets import load_dataset
# Load web crawl subset
icc = load_dataset("ThingsAI/Italian-Common-Corpus", data_files="data/icc-web.parquet", split="train")
# Load Wikipedia subset
wiki = load_dataset("ThingsAI/Italian-Common-Corpus", data_files="data/wiki-it-clean.parquet", split="train")
# Load everything
full = load_dataset("ThingsAI/Italian-Common-Corpus", split="train")
print(icc[0])
```
## Quality Pipeline
1. **Async crawling** — 20 parallel workers, rate-limited per domain
2. **Text extraction** — Trafilatura with precision mode
3. **Spam detection** — 13 regex patterns + statistical analysis
4. **Quality scoring** — Lexical richness, sentence structure, punctuation (0-100)
5. **Deduplication** — MD5 hash + partial content matching
6. **Wikipedia cleaning** — Section removal (Notes, Bibliography, See also, External links)
Only documents scoring ≥50/100 are included.
## License
CC-BY-4.0
## Citation
```bibtex
@dataset{modotai_icc_2026,
author = {ModotAI},
title = {Italian-Common-Corpus},
year = {2026},
publisher = {HuggingFace},
url = {https://huggingface.co/datasets/ThingsAI/Italian-Common-Corpus}
}
```
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