Description:
hepai 1.1.10
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HepAI Library
This is HepAI python library, the AI platform can accelerate scientific research in multidisciplinary scenarios, simplify model iteration and flow, and is a common infrastructure for the development of AI algorithms and applications.
The HepAI platform itself is a software system that carries AI algorithm models, provides AI computing power, connects data channels, and conducts AI training.
The HepAI framework integrates classic and state-of-the-art (SOTA) artificial intelligence algorithms in the field of high-energy physics. One can access related algorithm models, datasets, and computational resources through a unified interface, making the application of AI simple and efficient.
News
[2024.05.16] v1.1.9 HepAI Client支持GPT-4o, 调用方法:
[2024.03.26] v1.0.21 Make LLM request like OpenAI via HepAI object.
[2023.10.24] v1.0.18 接入dalle文生图模型，调用方法教程见此处。
[2023.04.21] v1.0.7通过hepai使用GPT-3.5，hepai_api.md.
[2023.02.09] 基于ChatGPT的HaiChatGPT已上线，使用简单，无需梯子！详情查看：HaiChatGPT.
[2023.01.16] 华为NPU服务器上架，如有算法国产化需求，请查阅NPU文档。
[2022.10.20] HAI v1.0.6-Beta 第一个测试版本发布，4个算法和3个数据集
[2022.08.23] HAI v1.0.0
Tutorials
Quick Start to Using HepAI on Computing Clusters
Reconstruction and identification of atmospheric neutrinos in JUNO experiments using PointNet
Algorithm Zoo
Dataset Zoo
Quick start
pip install hepai --upgrade
hai -V # 查看版本
命令行使用
hai train <model_name> # 训练模型, 例如: hai train particle_transformer
hai eval <model_name>
python库使用
python库统一接口：
import hai
model = hai.hub.load('<model_name>') # 加载模型
config = model.config # 获取模型配置
config.batch_size = 32 # 修改配置
model.trian() # 训练模型
model.eval() # 评估模型
model.infer('<data>') # 模型推理
hai.train('particle_transformer')
部署和远程调用
跨语言、跨平台的模型部署和远程调用
服务端：
hai start server # 启动服务
客户端
pip install hai-client
import hai_client
hai = hai_client.HAI()
或其他支持gRPC的语言，详见deploy
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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