DeepKE-LLM 的安装 方法一:In-Context Learning 上下文学习 使用方法 方法二:Lora微调 数据 训练 KnowLM 预测 方法三:P-Tuning微调 训练 预测 参考 简介 DeepKE 作为一个全面的知识提取工具包,不仅在构建知识图谱方面展现出卓越性能,还针对多种场景(如cnSchema、低资源环境、文档级处理和多模态分析)提供了强大支持...
Please refer to DeepKE/example/llm/README.md to create a Python virtual environment, and activate the deepke-llm environment: conda activate deepke-llm mkdir results mkdir lora mkdir data Place the data in the directory ./data 🐐 3.2Model Here are some of the models supported by the code ...
大模型时代, DeepKE-LLM采用全新的环境依赖 conda create -n deepke-llm python=3.9 conda activate deepke-llm cd example/llm pip install -r requirements.txt 注意!!是example/llm文件夹下的 requirements.txt DeepKE DeepKE支持pip安装使用,下以常规关系抽取场景为例 DeepKE支持手动环境部署与容器部署,您可任选...
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在开始之前,请确保根据DeepKE/example/llm/README_CN.md中的指导创建了适当的Python虚拟环境。创建并配置好虚拟环境后,请通过以下命令激活名为 deepke-llm 的环境: conda activate deepke-llm mkdir results mkdir lora mkdir data 数据放在目录 ./data 中。 🐐 3.2模型 以下是本仓库代码支持的一些基础模型:[...
DeepKE-LLM 大模型时代, DeepKE-LLM采用全新的环境依赖 conda create -n deepke-llm python=3.9 conda activate deepke-llm cd example/llm pip install -r requirements.txt 注意!!是example/llm文件夹下的 requirements.txt DeepKE DeepKE支持pip安装使用,下以常规关系抽取场景为例 DeepKE支持手动环境部署与容器部...
[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction - DeepKE/example/llm/InstructKGC/ft_scripts/fine_chatglm.bash at main · zjunlp/DeepKE
大模型时代, DeepKE-LLM采用全新的环境依赖 conda create -n deepke-llm python=3.9 conda activate deepke-llm cd example/llm pip install -r requirements.txt 注意!!是example/llm文件夹下的 requirements.txt DeepKE DeepKE支持pip安装使用,下以常规关系抽取场景为例 DeepKE支持手动环境部署与容器部署,您可任选...
DeepKE-LLM In the era of large models, DeepKE-LLM utilizes a completely new environment dependency. conda create -n deepke-llm python=3.9 conda activate deepke-llm cd example/llm pip install -r requirements.txt Please note that therequirements.txtfile is located in theexample/llmfolder. ...
llm / InstructKGC / README_CN.md README_CN.md43.65 KB 一键复制编辑原始数据按行查看历史 guihonghao提交于1年前.update English| 简体中文 InstructionKGC-指令驱动的自适应知识图谱构建 🎯 1.任务目标 📊 2.数据 2.1信息抽取模板 2.2现有数据集 ...