Cancel Job

Prerequisites

Before you can cancel a customization job, make sure that you have:

• Obtained the base URL of your NeMo Platform.

• Set the NMP_BASE_URL environment variable to your NeMo Platform endpoint

export NMP_BASE_URL="https://your-nmp-base-url"

---

To Cancel a Customization Job

Running jobs may be cancelled. A cancelled job does not upload checkpoints. You need the job’s name and workspace; you can get these from List Active Jobs.

Use the SDK to cancel a customization job:

import os
from nemo_platform import NeMoPlatform

# Initialize the client
client = NeMoPlatform(
    base_url=os.environ.get("NMP_BASE_URL", "http://localhost:8080"),
    workspace="default",
)

# Cancel a customization job (use the job name and workspace from List Active Jobs)
job_name = "my-sft-job"
workspace = "default"
cancelled_job = client.customization.jobs.cancel(name=job_name, workspace=workspace)

print(f"Job {cancelled_job.name} has been cancelled")
print(f"Current status: {cancelled_job.status}")
print(f"Updated at: {cancelled_job.updated_at}")

Example Response

{
  "name": "my-sft-job",
  "workspace": "default",
  "id": "job-abc123def456",
  "status": "cancelled",
  "spec": {
    "model": "default/llama-3-2-1b",
    "dataset": "fileset://default/my-training-dataset",
    "training": {
      "type": "sft",
      "batch_size": 16,
      "epochs": 3,
      "learning_rate": 0.00001,
      "max_seq_length": 4096,
      "parallelism": {
        "num_gpus_per_node": 2,
        "tensor_parallel_size": 2
      }
    },
    "output": {"name": "my-finetuned-llama", "type": "model", "fileset": "my-finetuned-llama-a1b2c3d4e5f6"}
  },
  "created_at": "2026-02-09T10:30:00.000Z",
  "updated_at": "2026-02-09T10:35:00.000Z"
}