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Easy-to-use Information Extraction Framework

Project description

FastIE

此项目为开源文本分类、实体抽取、关系抽取和事件抽取模型的训练和推理提供统一的框架,具有以下特性

  • ✨ 支持多种开源文本分类、实体抽取、关系抽取和事件抽取模型

  • 👑 支持百度 UIE 模型的训练和推理

  • 🚀 统一的训练和推理框架

  • 🎯 集成对抗训练方法,简便易用

📢 更新日志

  • 【2024.8.30】 发布初始版本

📦 快速安装

pip 安装

pip install --upgrade fastie

源码安装

git clone https://github.com/xusenlinzy/FastIE.git
pip install -e .

🚀 模型训练

实体抽取

cd examples/named_entity_recognition
fastie-cli train global_pointer.yaml

具体参数详见 named_entity_recognition

关系抽取

cd examples/relation_extraction
fastie-cli train gplinker.yaml

具体参数详见 relation_extraction

事件抽取

cd examples/event_extraction
fastie-cli train gplinker.yaml

具体参数详见 event_extraction

📊 模型推理

本项目实现了对各类模型推理代码的封装,只需要4行代码即可推理!

from transformers import AutoModel, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("path_to_model", trust_remote_code=True)
model = AutoModel.from_pretrained("path_to_model", trust_remote_code=True)

print(model.predict(tokenizer, "因肺过度充气,常将肝脏推向下方。"))

一键启动模型接口或DEMO

# fastie-cli api --model_name_or_path path_to_model --port 9000
fastie-cli demo --model_name_or_path path_to_model --port 9000

致谢

本项目受益于 LLaMA-Factory,感谢以上诸位作者的付出。

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