metadata
license: apache-2.0
datasets:
- datajuicer/redpajama-wiki-refined-by-data-juicer
- datajuicer/redpajama-arxiv-refined-by-data-juicer
- datajuicer/redpajama-c4-refined-by-data-juicer
- datajuicer/redpajama-book-refined-by-data-juicer
- datajuicer/redpajama-cc-2019-30-refined-by-data-juicer
- datajuicer/redpajama-cc-2020-05-refined-by-data-juicer
- datajuicer/redpajama-cc-2021-04-refined-by-data-juicer
- datajuicer/redpajama-cc-2022-05-refined-by-data-juicer
- datajuicer/redpajama-cc-2023-06-refined-by-data-juicer
- datajuicer/redpajama-pile-stackexchange-refined-by-data-juicer
- datajuicer/redpajama-stack-code-refined-by-data-juicer
- datajuicer/the-pile-nih-refined-by-data-juicer
- datajuicer/the-pile-europarl-refined-by-data-juicer
- datajuicer/the-pile-philpaper-refined-by-data-juicer
- datajuicer/the-pile-pubmed-abstracts-refined-by-data-juicer
- datajuicer/the-pile-pubmed-central-refined-by-data-juicer
- datajuicer/the-pile-freelaw-refined-by-data-juicer
- datajuicer/the-pile-hackernews-refined-by-data-juicer
- datajuicer/the-pile-uspto-refined-by-data-juicer
News
Our first data-centric LLM competition begins! Please visit the competition's official websites, FT-Data Ranker (1B Track, 7B Track), for more information.
Introduction
This is a reference LLM from Data-Juicer.
The model architecture is LLaMA-1.3B and we adopt the OpenLLaMA implementation. The model is pre-trained on 150B tokens of Data-Juicer's refined RedPajama and Pile, and 4.7B tokens of Data-Juicer refined instruct data. It achieves an average score of 36.76 over 16 HELM tasks, improved the OpenLLaMA-DJ-150B by 2.55 point.
For more details, please refer to our paper.