DeePMD Router
SkillAI & modelsRoute DeePMD-kit requests to training or inference sub-skills. Use when the user requests machine learning potentials, DeePMD, DPA-3, DP models, or MLIP training.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the DeePMD Router skill
What this skill tells your AI
The instructions your AI receives, as published by hello-qm/catgo-lrg in server/catgo/workflow/skills/deepmd/SKILL.md and read by ahel’s review.
Route DeePMD-kit requests to the appropriate sub-skill.
Routing Table
| User intent | Route to |
|---|---|
| Train a new DP model (DPA-3, se_e2_a, fine-tune) | train/SKILL.md |
| Run inference, predict energy/forces, evaluate model | inference/SKILL.md |
| Run MD with a DP model | ../lammps/deepmd/SKILL.md |
Shared Policies
- Data format — DeePMD training data must be in dpdata format. If user has VASP/QE output, route through
../data/dpdata/SKILL.mdfirst. - Model selection — DPA-3 is the recommended architecture for new projects. Use se_e2_a only for legacy compatibility.
- GPU requirement — training requires GPU. Inference can run on CPU but is much faster on GPU.
- Validation split — always hold out 10-20% of data for validation. Never train on all data.
Quick Decision Guide
- "Train a potential" / "fit a model" / "DPA-3" →
train/SKILL.md - "Fine-tune" / "transfer learn" →
train/SKILL.md(fine-tune section) - "Predict" / "evaluate" / "test model" →
inference/SKILL.md - "Run MD with DP" / "LAMMPS + DeePMD" →
../lammps/deepmd/SKILL.md - "Convert data" / "prepare training data" →
../data/dpdata/SKILL.md
Signals
- GitHub stars
- 196
- Forks
- 23
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
deepmd-router- Source
- github.com/hello-qm/catgo-lrg