Update README.md

README.md

@@ -69,20 +69,30 @@ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ## Sagemaker Endpoint I/O Example
 
 
-```js
-{
+```py
+payload = {
     "inputs": "### Schema and the Natural Language Query:\nCREATE TABLE stadium (\n    stadium_id number,\n    location text,\n    name text,\n    capacity number,\n    highest number,\n    lowest number,\n    average number\n)\n\nCREATE TABLE singer (\n    singer_id number,\n    name text,\n    country text,\n    song_name text,\n    song_release_year text,\n    age number,\n    is_male others\n)\n\nCREATE TABLE concert (\n    concert_id number,\n    concert_name text,\n    theme text,\n    stadium_id text,\n    year text\n)\n\nCREATE TABLE singer_in_concert (\n    concert_id number,\n    singer_id text\n)\n\n-- Using valid SQLite, answer the following questions for the tables provided above.\n\n-- What is the maximum, the average, and the minimum capacity of stadiums ?",
     "parameters": {
         "maxNewTokens": 512,
         "topP": 0.9,
-        "temperature": 0.2,
-        "decoderInputDetails": true,
-        "details": true
+        "temperature": 0.2
     }
 }
+
+client = boto3.client('runtime.sagemaker')
+endpoint_name = 'deployed_model_name'
+response = client.invoke_endpoint(
+    EndpointName=endpoint_name,
+    ContentType='application/json',
+    Body=json.dumps(payload).encode('utf-8'),
+)
+response = response["Body"].read().decode("utf8")
+response = json.loads(response)
+print(response[0]['generated_text'])
+
 ```
 
-```js
+```json
 {
     "body": [
         {