初始化项目，由ModelHub XC社区提供模型
Model: Xunzillm4cc/Xunzi-Qwen1.5-4B Source: Original Platform
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README.md
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# 荀子系列大语言模型
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随着科技的飞速发展，人工智能已深入到各个领域。为响应古籍活化利用号召，推动大语言模型与古籍处理深度融合，以古籍智能化的研究为目的，本项目推出了一系列古籍处理领域大语言模型：荀子古籍大语言模型。荀子不仅是我国先秦时期伟大的朴素唯物主义的思想家，也是一位散文大家。他在语言学理论的阐述上又是一位开拓者、奠基人。荀子系列专为古籍智能处理而设计，这一系列模型的推出将推动古籍研究与保护工作的新发展，提高中华传统文化传承的效率与质量。
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本次荀子系列模型开源包括两个部分：基座模型[**XunziALLM**](https://modelscope.cn/models/Xunzillm4cc/Xunzi-Qwen)与对话模型[**XunziChat**](https://modelscope.cn/models/Xunzillm4cc/Xunzi-Qwen-Chat)，模型的调用方式与阿里云的Qwen系列大模型一致。
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## 荀子系列模型亮点：
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* 古籍智能标引，荀子模型具备强大的古籍文献标引能力，能够对古籍中的内容进行高质量主题标引，帮助研究人员快速了解文章主题。
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* 古籍信息抽取，荀子模型能够自动从古籍中抽取关键信息，如人物、事件、地点等，大大节省了研究人员的信息整理时间。
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* 诗歌生成：荀子模型还具备诗歌生成的能力，能够根据给定的主题或关键词，自动生成符合语法规则和韵律要求的古诗，为诗词爱好者提供创作灵感。
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* 古籍高质量翻译：对于那些难以理解的古籍文献，荀子模型能够提供高质量的翻译服务，帮助研究人员更好地理解原文含义。
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* 阅读理解：荀子模型能够对给出的古文文本进行分析解释，实现对古籍文本的自动阅读。
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* 词法分析：荀子模型可以完成古籍文本的自动分词和词性标注，能够有效提升语言学工作者的研究效率。
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* 自动标点：荀子大模型可以快速完成古籍文本的断句和标点，提升研究者以及业余爱好者对古籍文本的阅读体验。
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由于我们同时发布了基座模型，用户也可以根据自己的需求，使用本地的训练语料微调荀子基座模型，使得其能够在古籍下游处理任务上取得更佳的处理性能。
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## 声明：
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大语言模型庞大的参数量也带来了更多的随机性，虽然我们在训练数据选取时已经尽可能保证了数据的合规性，但由于数据和模型的复杂性，仍有可能存在一些无法避免的问题。因此，如果由于使用本开源模型而导致的各种问题，包括但不限于数据安全问题、公共舆论风险，或模型被误导、滥用、传播或不当利用所带来的任何风险和问题，我们将不承担任何责任。
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此外，根据国家网信办等七部门联合发布的[《生成式人工智能服务管理暂行办法》](http://www.cac.gov.cn/2023-07/13/c_1690898327029107.htm)，在训练、使用本模型以及其他生成式模型，请依据相关法律法规，为构建和谐、健康、可持续的生成式人工智能社区共同努力。
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因此，如果由于使用本开源模型而导致的任何问题，包括但不限于数据安全问题、公共舆论风险，或模型被误导、滥用、传播或不当利用所带来的任何风险和问题，我们将不承担任何责任。
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如果您在使用模型时遇到了任何问题，欢迎联系我们(letz999@163.com)
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```bash
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git clone https://www.modelscope.cn/Xunzillm4cc/Xunzi-Qwen1.5-4B.git
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config.json
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||||
"model.norm.weight": "model-00002-of-00002.safetensors"
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||||
}
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||||
}
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||||
@@ -0,0 +1,3 @@
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||||
version https://git-lfs.github.com/spec/v1
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oid sha256:f552622583d640fe5e4e13979af01b5c926d58557be9d0787ba9cfaaa15288a4
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20
special_tokens_map.json
Normal file
20
special_tokens_map.json
Normal file
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||||
{
|
||||
"additional_special_tokens": [
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||||
"<|im_start|>",
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44
tokenizer_config.json
Normal file
44
tokenizer_config.json
Normal file
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{
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||||
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"chat_template": "{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ system_message }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ content }}{% elif message['role'] == 'assistant' %}{{ content + '<|endoftext|>' }}{% endif %}{% endfor %}",
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train_results.json
Normal file
7
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Normal file
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trainer_log.jsonl
Normal file
159
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Normal file
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vocab.json
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vocab.json
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Load Diff
Reference in New Issue
Block a user