yxdyc's picture
Update README.md
69e09e0
|
raw
history blame
1.65 kB
---
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
---
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 50B tokens of Data-Juicer's refined RedPajama and Pile.
It achieves an average score of 31.21 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).
![exp_llama](https://img.alicdn.com/imgextra/i2/O1CN019WtUPP1uhebnDlPR8_!!6000000006069-2-tps-2530-1005.png)