Tensorflow.js tf.loadModel() from localStorage not working - tensorflow.js

Question

I am having problems using tf.loadModel(). I have built and trained a model and now I want to store it to the localStorage of my browser and retrieve it again.
path = 'localstorage://my-model'
const saveResults = model.saveModel(path)
var loadedModel;
tf.loadModel(path).then((data) => {loadedModel = data})
loadedModel is now i Tensorflow model object. But it is now identical to a newly created tf.sequential(). Below are the properties of loadedModel as presented by console.log(loadedModel). What could be the problem? I am fairly new at Promises, so the problem might lay there, however I have been experimenting with this for quite some time without making any progress.
I have checked tf.io.listModels() to check that the model indeed has been saved and that the file is not corrupted.
_addedWeightNames: Array []
_built: false.
_callHook: null.
_losses: Array [].
_nonTrainableWeights: Array [].
_stateful: false.
_trainableWeights: Array []
_updatable: true
_updates: Array []
activityRegularizer: null
containerNodes: Set []
feedInputNames: Array []
feedInputShapes: Array []
feedOutputNames: Array []
id: 33
inboundNodes: Array [ {…}, {…} ]
initialWeights: null
inputLayers: Array []
inputLayersNodeIndices: Array []
inputLayersTensorIndices: Array []
inputNames: Array []
inputSpec: null
inputs: Array [ {…} ]
internalInputShapes: Array []
internalOutputShapes: Array []
layers: Array(6) [ {…}, {…}, {…}, … ]
layersByDepth: Object { }
name: "sequential_5"
nodesByDepth: Object { }
outboundNodes: Array []
outputLayers: Array []
outputLayersNodeIndices: Array []
outputLayersTensorIndices: Array []
outputNames: Array []
outputs: Array [ {…} ]
supportsMasking: false
trainable: true
While console.log(model) shows this:
_addedWeightNames: Array []
_built: true
_callHook: null
_losses: Array []
_nonTrainableWeights: Array []
_stateful: false
_trainableWeights: Array []
_updatable: true
_updates: Array []
activityRegularizer: null
containerNodes: Set(7) [ "dense_Dense1_ib-0", "flatten_Flatten1_ib-0", "max_pooling2d_MaxPooling2D2_ib-0", … ]
feedInputNames: Array []
feedInputShapes: Array []
feedOutputNames: Array []
id: 0
inboundNodes: Array [ {…}, {…} ]
initialWeights: null
inputLayers: Array [ {…} ]
inputLayersNodeIndices: Array [ 0 ]
inputLayersTensorIndices: Array [ 0 ]
inputNames: Array [ "conv2d_Conv2D1_input" ]
inputSpec: null
inputs: Array [ {…} ]
internalInputShapes: Array []
internalOutputShapes: Array []
layers: Array(6) [ {…}, {…}, {…}, … ]
layersByDepth: Object { }
loss: "categoricalCrossentropy"
metrics: Array [ "accuracy" ]
metricsNames: Array [ "loss", "acc" ]
metricsTensors: Array [ (2) […] ]
model: Object { _stateful: false, id: 8, supportsMasking: false, … }
name: "sequential_1"
nodesByDepth: Object(7) [ (1) […], (1) […], (1) […], … ]
optimizer: Object { learningRate: 0.15, c: {…} }
outboundNodes: Array []
outputLayers: Array [ {…} ]
outputLayersNodeIndices: Array [ 0 ]
outputLayersTensorIndices: Array [ 0 ]
outputNames: Array [ "dense_Dense1" ]
​outputs: Array [ {…} ]
supportsMasking: false
trainable: true