---
title: "Get detailed information about a model."
method: GET
path: "/di/v1/models/{model_id}/kill"
tags: ["Models"]
---

# Get detailed information about a model.

`GET /di/v1/models/{model_id}/kill`

Get detailed information about a model such as training status.

## Path parameters

- `model_id` string, required

## Response `200`

Detailed model and training information.

- Model
  - `model_id` string — A unique id of the deep learning model.
  - `location` string — Location of the model to retrieve it.
  - `name` string — The name of the deep learning model.
  - `description` string — Detailed description of deep learning model.
  - `framework` Framework
    - `name` string — the name of the deep learning framework (e.g. caffe, torch, tensorflow)
    - `version` string — the version of the specific framework to use.
  - `training` Training
    - `command` string — the command invoked for running the training. This is specific to the DL framework
    - `size` string — the pre-configured deployment size to used for training. The is used instead of directly specifying CPU, GPU, memory and learners.
    - `cpus` number, double — Number of CPUs required
    - `gpus` number, double — Number of CPUs required
    - `memory` number, double — Amount of memory required
    - `memory_unit` 'MiB' | 'MB' | 'GiB' | 'GB' — Memory unit (default: MiB)
    - `learners` integer — Number of learners required.
    - `input_data` string[] — Input data to the training, such as training data, pre-trained model. The input is specified as references to the data_store ids that contain the data.
    - `output_data` string[] — Output data of the training, such as trained models. The output is specified as references to the data_store ids that contain the data.
    - `training_status` TrainingStatus
      - `status` string — Status of the training.
      - `status_description` string — Description of the training status.
      - `submitted` string — Training submission timestamp (Format: yyyy-MM-dd'T'HH:mm:ss.SSS'Z')
      - `completed` string — Training completion timestamp (Format: yyyy-MM-dd'T'HH:mm:ss.SSS'Z')
      - `status_message` string — A human readable message description of the training status.
      - `error_code` string — A code identifying the cause of a status message.
  - `data_stores` Datastore[]
    - `data_store_id` string — the id of the data store as defined in the manifest.
    - `type` string — the type of the data store as defined in the manifest.
    - `connection` object
    - `Fields` object
  - `job_namespace` string — job's namespace.
  - `user_id` string — user name.
  - `pss` string — Count of Param Server
  - `ps_cpu` string — Count of Param Server
  - `ps_image` string — Count of Param Server
  - `ps_memory` string — Count of Param Server
  - `JobAlert` string — Job Alert String.
  - `JobType` string — Job Type.
  - `expRunId` string — Experiment Run Id
  - `expName` string — Experiment Name
  - `fileName` string — Code File's Name
  - `filePath` string — Code File's Path
  - `submission_timestamp` string — submission timestamp of the job.
  - `completed_timestamp` string — completed timestamp of the job
  - `TFosRequest` TFosRequest
    - `py_file` Fields[] — PyFiles Fields.
      - `hdfs` string — HDFS Path.
      - `resource_id` string — BML Resource ID.
      - `version` string — BML Resource Version.
    - `Archives` Fields[] — Archives Fields.
      - `hdfs` string — HDFS Path.
      - `resource_id` string — BML Resource ID.
      - `version` string — BML Resource Version.
    - `EntryPoint` Fields — TFOS Archives & PyFile Fields
      - `hdfs` string — HDFS Path.
      - `resource_id` string — BML Resource ID.
      - `version` string — BML Resource Version.
    - `TensorflowEnv` Fields — TFOS Archives & PyFile Fields
      - `hdfs` string — HDFS Path.
      - `resource_id` string — BML Resource ID.
      - `version` string — BML Resource Version.
    - `Executors` string — Queue Setting Executor Number.
    - `ExecutorCores` string — Queue Setting Executor Cores.
    - `ExecutorMemory` string — Queue Setting Executor Memory.
    - `Queue` string — Queue Setting.
    - `DriverMemory` string — Queue Setting Driver Memory.
    - `Command` string — Experiment Description.
  - `proxy_user` string — proxy user of job
  - `job_params` string — algorithm of training job
  - `api_type` string — api type of xgboost or lightgbm
  - `data_set` DataSet
    - `training_data_path` string — the path of training data set.
    - `testing_data_path` string — the path of testing data set
    - `validation_data_path` string — the path of validation data set.
    - `training_label_path` string — the path of training data label.
    - `testing_label_path` string — the path of testing data label.
    - `validation_label_path` string — the path of validation data label.
  - `code_selector` string — code_selector type file
  - `submit_id` string — submit_id describe user submit

## Other responses

- `401` — Unauthorized
- `404` — Model with the given ID not found.

---

[API](https://skmtc.net/webankfintech/apis/prophecis-rest-service.md) · [All operations](https://skmtc.net/webankfintech/apis/prophecis-rest-service/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/webankfintech/prophecis-rest-service/versions/41a1038b5854/schema)