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POST
/
api
/
{projectId}
/
jobs
/
deploy-pretrained-model
Deploy pretrained model
curl --request POST \
  --url https://studio.edgeimpulse.com/v1/api/{projectId}/jobs/deploy-pretrained-model \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data '
{
  "modelFileBase64": "<string>",
  "modelFileType": "tflite",
  "deploymentType": "<string>",
  "modelInfo": {
    "input": {
      "inputType": "time-series",
      "frequencyHz": 123,
      "windowLengthMs": 123
    },
    "model": {
      "modelType": "classification",
      "labels": [
        "<string>"
      ]
    }
  },
  "engine": "tflite",
  "representativeFeaturesBase64": "<string>",
  "deployModelType": "int8",
  "useConverter": "onnx-tf",
  "overrideInputShape": [
    123
  ]
}
'
{
  "success": true,
  "id": 12873488112,
  "error": "<string>"
}

Authorizations

​
x-api-key
string
header
required

Path Parameters

​
projectId
integer
required

Project ID

Query Parameters

​
impulseId
integer

Impulse ID. If this is unset then the default impulse is used.

Body

application/json
​
modelFileBase64
string
required

A base64 encoded pretrained model

​
modelFileType
enum<string>
required
Available options:
tflite,
onnx,
saved_model,
lgbm,
xgboost,
pickle,
ngboost
​
deploymentType
string
required

The name of the built target. You can find this by listing all deployment targets through listDeploymentTargetsForProject (via GET /v1/api/{projectId}/deployment/targets) and see the format type.

​
modelInfo
object
required
​
engine
enum<string>
Available options:
tflite,
tflite-eon,
tflite-eon-ram-optimized,
tensorrt,
tensaiflow,
drp-ai,
tidl,
akida,
syntiant,
memryx,
neox,
ethos-linux,
st-aton,
ceva-npn,
nordic-axon
​
representativeFeaturesBase64
string

A base64 encoded .npy file containing the features from your validation set (optional for onnx and saved_model) - used to quantize your model.

​
deployModelType
enum<string>
Available options:
int8,
float32
​
useConverter
enum<string>

Optional, use a specific converter (only for ONNX models).

Available options:
onnx-tf,
onnx2tf
​
overrideInputShape
integer[]

Optional for ONNX files: overrides the input shape of the model. This is highly suggested if the model has dynamic dimensions. If this field is not set, then all dynamic dimensions will be set to '1'.

Response

200 - application/json

OK

​
success
boolean
required

Whether the operation succeeded

​
id
integer
required

Job identifier. Status updates will include this identifier.

Example:

12873488112

​
error
string

Optional error description (set if 'success' was false)