Update docs/Researcher/scheduling/node-level-scheduler.md

Author: jasonnovichRunAI

docs/Researcher/scheduling/node-level-scheduler.md

@@ -9,7 +9,7 @@ date: 2024-Apr-4
 
 The Node Level Scheduler optimizes the performance of your pods and maximizes the utilization of GPUs by making optimal local decisions on GPU allocation to your pods. While the Cluster Scheduler chooses the specific node for a POD, but has no visibility to node’s GPUs internal state, the Node Level Scheduler is aware of the local GPUs states and makes optimal local decisions such that it can optimize both the GPU utilization and pods’ performance running on the node’s GPUs.
 
-Node Level Scheduler applies to all workload types, but will best optimize the performance of burstable workloads, giving those more GPU memory than requested and up to the limit specified. Be aware, burstable workloads are always susceptible to an OOM Kill signal if the owner of the excess memory requires it back. This means that using the Node Level Scheduler with Inference or Training workloads may cause pod preemption. Interactive workloads that are using notebooks behave differently since the OOM Kill signal will cause the GPU process to exit but not the notebook, hence keeping the Interactive pod running and retrying to attach a GPU again. This makes Interactive workloads with notebooks a great use case for burstable workloads and Node Level Scheduler.
+Node Level Scheduler applies to all workload types, but will best optimize the performance of burstable workloads, giving those more GPU memory than requested and up to the limit specified. Be aware, burstable workloads are always susceptible to an OOM Kill signal if the owner of the excess memory requires it back. This means that using the Node Level Scheduler with Inference or Training workloads may cause pod preemption. Interactive workloads that are using notebooks behave differently since the OOM Kill signal will cause the Notebooks' GPU process to exit but not the notebook itself. This keeps the Interactive pod running and retrying to attach a GPU again. This makes Interactive workloads with notebooks a great use case for burstable workloads and Node Level Scheduler.
 
 ## Interactive Notebooks Use Case