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---
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](https://tianchi.aliyun.com/competition/entrance/532157), [7B Track](https://tianchi.aliyun.com/competition/entrance/532158)), for more information.
## Introduction
This is a reference LLM from [Data-Juicer](https://github.com/alibaba/data-juicer).
The model architecture is LLaMA-1.3B and we adopt the [OpenLLaMA](https://github.com/openlm-research/open_llama) implementation.
The model is pre-trained on 100B tokens of Data-Juicer's refined RedPajama and Pile.
It achieves an average score of 33.07 over 16 HELM tasks, beating LLMs trained on original RedPajama and Pile datasets.
For more details, please refer to our [paper](https://arxiv.org/abs/2309.02033).
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