// Python
model = app.models.get('c1a2ac2adba0204d859fb89fd44d6ac9')
text = "This is a text string"
model.predict([text])

// JS
app.models.predict("c1a2ac2adba0204d859fb89fd44d6ac9,"This is a text string").then(
   function(response) {
     // do something with response
   },
  function(err) {
     // there was an error
   }
 );

// cURL
curl -X POST https://api.clarifai.com/v2/models/{c1a2ac2adba0204d859fb89fd44d6ac9}/versions/{version
_id}/outputs \
   -H 'Authorization: Key YOUR_API_KEY' \
   -H "Content-Type: application/json" \
   -d '
   {
     "inputs": [
       {
         "data": {
           "text": {
             "raw": "This is a text string"
           }
         }
       }
     ]
   }'

// Response
{ "status":
 { "code": 10000,
   "description": "Ok",
   "req_id": "req_id"
 },
 "outputs": [
   {"id": "input_id",
     "status": {
       "code": 10000,
       "description":"Ok"
     },
     "created_at": "DATE",
     "model": {
       "id" : "ifjaow;f",
       "name": "owiajefoiaw",
       "created_at": "DATE",
       "app_id": "app_id",
       "output_info": {
        "output_config": {
           "concepts_mutually_exclusive": false,
           "closed_environment": true,
           "max_concepts": 0,
           "min_value": 0
         },
         "message": "Show output_info with: GET /models/{model_id}/output_info",
         "type": "concept",
         "type_ext": "concept"
       },
       "input_info":{},
       "train_info":{},
       "model_type_id": "embedding-classifier"
     },
     "input":{
       "id":"13bfb782134e44e98a7955c98da7d490",
       "data":{
         "text":{
           "raw":"this is a text string",
         }
       }
     },
     "data":{
       "concepts":[
         {"id":"CONCEPT_ID",
         "name":"CONCEPT_NAME",
         "value":0.99375314,
         "app_id":"APP_ID"
         },
       ]
     }
   }
 ]
}