If Node.js interface is installed, one can use the Node.js interface for model inference, which is a wrapper of the header-only C++ API.
A simple example is shown below.
const deepmd = require("deepmd-kit");
const dp = new deepmd.DeepPot("graph.pb");
const coord = [1., 0., 0., 0., 0., 1.5, 1., 0., 3.];
const atype = [1, 0, 1];
const cell = [10., 0., 0., 0., 10., 0., 0., 0., 10.];
const v_coord = new deepmd.vectord(coord.length);
const v_atype = new deepmd.vectori(atype.length);
const v_cell = new deepmd.vectord(cell.length);
for (var i = 0; i < coord.length; i++) v_coord.set(i, coord[i]);
for (var i = 0; i < atype.length; i++) v_atype.set(i, atype[i]);
for (var i = 0; i < cell.length; i++) v_cell.set(i, cell[i]);
var energy = 0.0
var v_forces = new deepmd.vectord();
var v_virials = new deepmd.vectord();
energy = dp.compute(energy, v_forces, v_virials, v_coord, v_atype, v_cell);
console.log("energy:", energy);
console.log("forces:", [...Array(v_forces.size()).keys()].map(i => v_forces.get(i)));
console.log("virials:", [...Array(v_virials.size()).keys()].map(i => v_virials.get(i)));
Energy, forces, and virials will be printed to the screen.