- DeePMD-kit v3有望在物理、化学和材料科学中得到更广泛的应用。 数据可用性: - 源代码可在GitHub上找到: GitHub - deepmodeling/deepmd-kit: A deep learning package for many-body potential energy representation and molecular dynamicsgithub.com/deepmodeling/deepmd-kit - 性能测试代码可在GitHub上找到:...
在DeePMD-kit v3最新的2024Q1分支版本(https://github.com/deepmodeling/deepmd-kit/tree/2024Q1)中,还包含了如下的新功能支持,主要包括: DeepSpin升级,PyTorch版本现已支持包括DPA2在内的所有descriptor,可以结合如type embedding等模型结构,获得更高精度的磁性模型,为带磁性体系的研究推波助澜,输入案例见https://...
an advanced version that enables deep potential models with TensorFlow, PyTorch, or JAX backends. Additionally, DeePMD-kit v3 introduces support for theDPA-2 model, a novel architecture optimized for large atomic models. This release enhances plugin mechanisms, making integrating ...
In addition to building up potential energy models, DeePMD-kit can also be used to build up coarse-grained models. In these models, the quantity that we want to parameterize is the free energy, or the coarse-grained potential, of the coarse-grained particles. See theDeePCG paperfor more de...
v2.2.6 Find DeePMD-kit C/C++ library from CMake Create a model Atom Type Embedding Coding Conventions CI/CD Python API OP API C++ API C API Core API Class Hierarchy File Hierarchy Full API Namespaces Classes and Structs Unions Functions ...
With DeePMD-kit v3, we have expanded support to include two additional backends alongside TensorFlow: the PyTorch backend and the framework-independent backend (dpmodel). The PyTorch backend adopts a highly modularized design to provide flexibility and extensibility. It ensures a consistent experience ...
Seeour v3 paperfor details of all features until v3.0. Please read theonline documentationfor how to install and use DeePMD-kit. The code is organized as follows: examples: examples. deepmd: DeePMD-kit python modules. source/lib: source code of the core library. ...
"DeePMD-kit Multi-task" = "deepmd.utils.argcheck:gen_args_multi_task" [project.entry-points."dpdata.plugins"] deepmd_driver = "deepmd.driver:DPDriver" [project.urls] Homepage = "https://github.com/deepmodeling/deepmd-kit" documentation = "https://docs.deepmodeling.com/projects/deepmd"...
近日,DeePMD-kit v3的首个alpha版本(v3.0.0a0)发布,支持在 TensorFlow 或 PyTorch 等后端框架展开训练,并支持DPA-2等大原子模型(LAM)。随着新学期的到来,为了帮助更多国内外新人用户快速上手使用 DeePMD-kit 软件,我们更新了「快速开始 DeePMD-kit」教程,助力大家以 Bohrium Notebook 形式在云端动手实战。我们将在...
DeePMD-kit is a package written in Python/C++, designed to minimize the effort required to build deep learning-based models of interatomic potential energy and force field and to perform molecular dynamics (MD). This brings new hopes to addressing the accuracy-versus-efficiency dilemma in molecular...