---
title: "Get a list of available deep learning models."
method: GET
path: "/di/v1/models"
tags: ["Models"]
---

# Get a list of available deep learning models.

`GET /di/v1/models`

Get a list of all available deep learning models and their configuration that a user can see.

## Query parameters

- `version` string
- `userid` string
- `namespace` string
- `page` string
- `size` string
- `clusterName` string
- `exp_id` string
- `exp_run_id` string

## Response `200`

List of deep learning models.

- ModelList
  - `models` 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
  - `pages` integer
  - `total` integer

## Other responses

- `401` — Unauthorized

---

[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)