Can someone please help me with my object detection attempt?

I tried to implement object detection but I am coming across an error saying "KeyNotFoundException: The given key 'nms' was not present in the dictionary."

Here is my current code:

using UnityEngine;
using Unity.Sentis;
using System.Collections;
using System.Collections.Generic;

public class StairDetection : MonoBehaviour
{
    public ModelAsset detectionModel;
    IWorker m_engineDetection;
    WebCamTexture webcamTexture;
    TensorFloat inputTensor;

    int modelLayerCount = 0;
    public int framesToExectute = 2;

    void Start()
    {
        Application.targetFrameRate = 60;
        var model = ModelLoader.Load(detectionModel);

        // Reshape to [8400, 5]
        model.layers.Add(new Unity.Sentis.Layers.Reshape("reshaped", "output", "8400,5"));

        // Slice for bounding boxes [8400, 4]
        model.layers.Add(new Unity.Sentis.Layers.Slice("sliceBoxes", "reshaped", "0,0", "8400,4"));

        // Slice for confidence scores [8400]
        model.layers.Add(new Unity.Sentis.Layers.Slice("sliceScores", "reshaped", "0,4", "8400,5"));

        model.layers.Add(new Unity.Sentis.Layers.NonMaxSuppression(
                    name: "nms",
                    boxes: "sliceBoxes",
                    scores: "sliceScores",
                    maxOutputBoxesPerClass: "10",  // Adjust as needed
                    iouThreshold: "0.5",           // Common value, adjust as needed
                    scoreThreshold: "0.3",         // Adjust as needed
                    centerPointBox: Unity.Sentis.Layers.CenterPointBox.Corners
                ));

        modelLayerCount = model.layers.Count;
        model.outputs = new List<string> { "nms" };

        m_engineDetection = WorkerFactory.CreateWorker(BackendType.GPUCompute, model);

        WebCamDevice[] devices = WebCamTexture.devices;
        webcamTexture = new WebCamTexture(Screen.width, Screen.height)
        {
            deviceName = devices[0].name
        };
        webcamTexture.Play();

        inputTensor = TensorFloat.Zeros(new TensorShape(1, 3, 640, 640));
    }
    bool executionStarted = false;
    IEnumerator executionSchedule;

    private void Update()
    {
        if (!executionStarted)
        {
            TextureConverter.ToTensor(webcamTexture, inputTensor, new TextureTransform());
            executionSchedule = m_engineDetection.StartManualSchedule(inputTensor);
            executionStarted = true;
        }

        bool hasMoreWork = false;
        int layersToRun = (modelLayerCount + framesToExectute - 1) / framesToExectute; // round up
        for (int i = 0; i < layersToRun; i++)
        {
            hasMoreWork = executionSchedule.MoveNext();
            if (!hasMoreWork)
                break;
        }

        if (hasMoreWork)
            return;

        var output = m_engineDetection.PeekOutput() as TensorFloat;
        if (output != null)
        {
            Debug.Log("Output shape: " + output.shape);
            Debug.Log(output.ToReadOnlyArray());
        }
        executionStarted = false;
    }
}

The object detection model I am using is YOLOv8n. Here is the input and output structure:
INPUTS
images
name: images
tensor: float32[1, 3, 640, 640]

OUTPUTS
output0
name: output0
tensor: float32 [1,5,8400]

I mostly just followed the depth detection sample code. This script is intended to be used for an AR app. Any help would be greatly appreciated. Thanks!

Start in the StairDetection.Start method, where the YOLOv8n output is reshaped, sliced, and passed to NonMaxSuppression. Compare the declared output0 shape with the boxes and scores supplied to Sentis, then run the script to verify that inference completes without the missing 'nms' key error and produces detection output.