CFGPT1-pt-7B

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<div style="text-align:center"> <!-- <img src="https://big-cheng.com/k2/k2.png" alt="k2-logo" width="200"/> --> <h2>📈 CFGPT: Chinese Financial Assistant with Large Language Model (CFGPT1-pt-7b)</h2> </div>

Introduction

We introduce CFGPT, an open-source language model trained by firstly further pretraining general LLMs on collected and cleaned Chinese finance text data (CFData-pt), including financial domain-specific data (announcement, finance articles, finance exams, finance news, finance research papers) and general data (Wikipedia), and secondly fine-tuning with knowledge-intensive instruction tuning data (CFData-sft). As for preliminary evaluation, we use CFBenchmark-Basic. CFGPT outperforms the baselines on objective and subjective tasks compared to several baseline models with similar parameters.

In this repository, we will share the further pretrained model.

• Pretrained Model: Full model weights after further pretraining with the chinese finance text corpus to comply with the InternLM model license.

How to Use

The CFGPT1-pt-7b is a pre-trained model, which has not undergone supervised fine-tuning with a instruction data. Therefore, it is not advisable to use this model for financial tasks. Please refer to CFGPT Github repo for further usage.

简介

CFGPT是一个开源的语言模型，首先通过在收集和清理的中国金融文本数据（CFData-pt）上进行继续预训练，包括金融领域特定数据（公告、金融文章、金融考试、金融新闻、金融研究论文）和通用数据（维基百科），然后使用知识密集的指导调整数据（CFData-sft）进行微调。 我们使用CFBenchmark-Basic进行初步评估。与几个具有相似参数的基线模型相比，CFGPT在识别，分类和生成任务上表现优越。

在这个仓库中，我们将分享以下继续预训练的模型。

• Pretrained Model: 在中国金融文本语料库上进行进一步预训练且符合InternLM模型许可的完整模型权重。

如何使用

这个模型是一个预训练的模型，还没有经历过指令数据库的有监督微调，因此不建议使用该模型执行相关金融任务。 具体使用，请参考CFGPT的Github仓库。