mC4

Parameter-efficient fine-tuning (PEFT) using labeled task data can significantly improve the performance of large language models (LLMs) on the downstream task. However, there are 7000 languages in the world and many of these languages lack labeled data for real-world language generation tasks.

Data and Resources

Cite this as

Kshitij Gupta (2025). Dataset: mC4. https://doi.org/10.57702/v6e39h1h

DOI retrieved: January 2, 2025

Additional Info

Field Value
Created January 2, 2025
Last update January 2, 2025
Defined In https://doi.org/10.48550/arXiv.2210.00320
Citation
  • https://doi.org/10.48550/arXiv.2311.09344
  • https://doi.org/10.48550/arXiv.2312.06134
  • https://doi.org/10.48550/arXiv.2110.05838
  • https://doi.org/10.48550/arXiv.2404.08191
Author Kshitij Gupta
Homepage https://huggingface.co/mT5