Get a training

Get the current state of a training.

Example cURL request:

curl -s \
  -H "Authorization: Token <paste-your-token-here>" \
  https://api.replicate.com/v1/trainings/zz4ibbonubfz7carwiefibzgga

The response will be the training object:

{
  "completed_at": "2023-09-08T16:41:19.826523Z",
  "created_at": "2023-09-08T16:32:57.018467Z",
  "error": null,
  "id": "zz4ibbonubfz7carwiefibzgga",
  "input": {
    "input_images": "https://example.com/my-input-images.zip"
  },
  "logs": "...",
  "metrics": {
    "predict_time": 502.713876
  },
  "output": {
    "version": "...",
    "weights": "..."
  },
  "started_at": "2023-09-08T16:32:57.112647Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/trainings/zz4ibbonubfz7carwiefibzgga",
    "cancel": "https://api.replicate.com/v1/trainings/zz4ibbonubfz7carwiefibzgga/cancel"
  },
  "model": "stability-ai/sdxl",
  "version": "da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf",
}

status will be one of:

• starting: the training is starting up. If this status lasts longer than a few seconds, then it's typically because a new worker is being started to run the training.
• processing: the train() method of the model is currently running.
• succeeded: the training completed successfully.
• failed: the training encountered an error during processing.
• canceled: the training was canceled by its creator.

In the case of success, output will be an object containing the output of the model. Any files will be represented as HTTPS URLs. You'll need to pass the Authorization header to request them.

In the case of failure, error will contain the error encountered during the training.

Terminated trainings (with a status of succeeded, failed, or canceled) will include a metrics object with a predict_time property showing the amount of CPU or GPU time, in seconds, that the training used while running. It won't include time waiting for the training to start.