deepmd-finetune-dpa3
byjinzhezenggroup· 38 skills
Fine-tune a DPA3 model in DeePMD-kit using the PyTorch backend. Use when the user wants to adapt a pre-trained DPA3 model to a new downstream dataset. Supports fine-tuning from a self-trained DPA3 model (.pt checkpoint), from a multi-task pre-trained model, or from a built-in pretrained model downloaded via dp pretrained download (e.g., DPA-3.1-3M, DPA-3.2-5M, DPA-3.3-1M). Covers single-task and multi-task fine-tuning workflows.
How to install deepmd-finetune-dpa3?
jinzhezenggroup/computational-chemistry-agent-skills/deepmd-finetune-dpa3
$npx -y skills add jinzhezenggroup/computational-chemistry-agent-skills --skill deepmd-finetune-dpa3Installs into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/jinzhezenggroup/computational-chemistry-agent-skills" --skill "jinzhezenggroup/computational-chemistry-agent-skills/deepmd-finetune-dpa3"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/jinzhezenggroup/computational-chemistry-agent-skills" that are relevant to the current task. Run `npx skills add "https://github.com/jinzhezenggroup/computational-chemistry-agent-skills"` and select the relevant skills, then follow their instructions.
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