deepmd-python-inference
OfficialInference for DeePMD-kit models in Python efficiently.
Authorjinzhezenggroup
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Load a trained DeePMD-kit model in Python and perform fast predictions of energy, forces, and virial for atomic configurations. It also covers descriptor evaluation and cross-model comparison using the DeepPot API, plus CLI tools for batch testing.
Core Features & Use Cases
- Inference: load PyTorch (.pth) or TensorFlow (.pb) models, or built-in pretrained models, and obtain energy, forces, and virial.
- Descriptor evaluation: compute atomic environment descriptors from configurations.
- Model comparison: compute model deviation across multiple models; batch evaluation for datasets.
- CLI testing: run dp test-like workflows for labeled data and benchmarking.
Quick Start
Run a Python script to load a trained or pretrained DeePMD-kit model and perform a simple inference on a sample configuration.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
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Please help me install this Skill: Name: deepmd-python-inference Download link: https://github.com/jinzhezenggroup/computational-chemistry-agent-skills/archive/main.zip#deepmd-python-inference Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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