List Fine-tuning Jobs - Archetype AI Documentation

curl "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs?model=newton&status=RUNNING&limit=20" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")

response = requests.get(
    "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs",
    headers={"Authorization": f"Bearer {api_key}"},
    params={"model": "newton", "status": "RUNNING", "limit": 20}
)

print(response.json())

const params = new URLSearchParams({ model: 'newton', status: 'RUNNING', limit: '20' });

const response = await fetch(
  `https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs?${params}`,
  {
    headers: {
      'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
    }
  }
);

const data = await response.json();
console.log(data);

{
  "object": "list",
  "data": [
    {
      "object": "fine_tuning.job",
      "id": "your-job-id",
      "name": "my-tune",
      "model": "newton",
      "created_at": 1765201323,
      "org_id": "your-org",
      "status": "RUNNING",
      "checkpoint_id": null,
      "fine_tuned_model": null,
      "finished_at": null,
      "outcome": null,
      "seed": 42,
      "user_provided_suffix": "v2",
      "training_files": ["fil_..."],
      "validation_files": ["fil_..."],
      "errors": []
    }
  ],
  "has_more": false
}

GET

fine_tuning

jobs

curl "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs?model=newton&status=RUNNING&limit=20" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")

response = requests.get(
    "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs",
    headers={"Authorization": f"Bearer {api_key}"},
    params={"model": "newton", "status": "RUNNING", "limit": 20}
)

print(response.json())

const params = new URLSearchParams({ model: 'newton', status: 'RUNNING', limit: '20' });

const response = await fetch(
  `https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs?${params}`,
  {
    headers: {
      'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
    }
  }
);

const data = await response.json();
console.log(data);

{
  "object": "list",
  "data": [
    {
      "object": "fine_tuning.job",
      "id": "your-job-id",
      "name": "my-tune",
      "model": "newton",
      "created_at": 1765201323,
      "org_id": "your-org",
      "status": "RUNNING",
      "checkpoint_id": null,
      "fine_tuned_model": null,
      "finished_at": null,
      "outcome": null,
      "seed": 42,
      "user_provided_suffix": "v2",
      "training_files": ["fil_..."],
      "validation_files": ["fil_..."],
      "errors": []
    }
  ],
  "has_more": false
}

Requires version 1.1.5 or later of the Archetype platform.

Overview

Returns a cursor-paginated list of fine-tuning jobs, sorted with the newest job first.

Request

string

Filter by model, e.g. newton.

string

Filter by training method, e.g. lora or head.

string

Filter by lifecycle status, e.g. RUNNING, COMPLETED, FAILED. A job that has not been dispatched yet is PENDING.

string

Filter by completion outcome (SUCCESS/PARTIAL/FAILED). Only completed jobs carry an outcome, so specifying a value for this parameter implicitly limits results to completed jobs. v1.1.5+

string

Case-insensitive search matched against the job name, suffix, and produced model name.

string

Forward cursor: return jobs older than the job with this ID. Pass the ID of the last job from the previous page to fetch the next page. Mutually exclusive with before.

string

Backward cursor: return jobs newer than the job with this ID. Pass the ID of the first job from the current page to fetch the previous page. Mutually exclusive with after.

integer

The maximum number of jobs to return (1–100).

Response

Returns a page of fine-tuning jobs.

string

The object type. Always list.

array

An array of the jobs for this page, sorted newest-first. Each item is a fine-tuning job object.

Show Fine-tuning job

The description of a single fine-tuning job.

string

required

The object type. Always fine_tuning.job.

string

required

The unique identifier of the fine-tuning job.

string

required

The human-readable name supplied when the job was created.

string

required

The base model being fine-tuned.

integer

required

The Unix timestamp (in seconds) at which the job was created.

string

required

The organization that owns the job.

string

required

The job’s current lifecycle stage. One of PENDING, ADMITTED, RUNNING, COMPLETED, FAILED, PREEMPTED, CANCELLED, PAUSED, INTERRUPTED.

string

If and only if the job’s status is COMPLETED, this property’s value indicates how the job completed. It is set once upon completion and is never set for a job which is not completed; for incomplete jobs, this value is always omitted. v1.1.5+For completed jobs, the following values are possible:

Value	Description
`SUCCESS`	None of the job’s inputs failed.
`PARTIAL`	At least one of the job’s inputs failed, but the job still produced at least one artifact (either a `job_outputs` entry or a `checkpoints` entry).
`FAILED`	At least one input failed, and the job produced no artifacts at all (no outputs and no checkpoints).

array

required

Identifiers of the training files used to train the model.

array

required

Identifiers of the files used to evaluate the model during training.

array

required

When the job has failed, this array lists the error(s) that occcurred, as the platform error envelope (a list of {code, message, suggestion, error_uid}). Empty while the job is queued/running or on success.

string

The ID of the checkpoint the job was started from, or null if it trained from the base model.

string

Name of the model produced by the job. This is only available once training has succeeded; until then, this value is null.

integer

The Unix timestamp (in seconds) at which the job finished, or null if it is not yet complete.

string

For a COMPLETED job, this value indicates whether it succeeded fully (SUCCESS), partially (PARTIAL), or produced nothing (FAILED). For any job that hasn’t completed, this value is null.

integer

The random seed used for the job.

string

The suffix supplied on the request, applied to the fine-tuned model’s name.

boolean

Whether more jobs exist beyond this page.

curl "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs?model=newton&status=RUNNING&limit=20" \
  -H "Authorization: Bearer $ATAI_API_KEY"

import requests
import os

api_key = os.environ.get("ATAI_API_KEY")

response = requests.get(
    "https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs",
    headers={"Authorization": f"Bearer {api_key}"},
    params={"model": "newton", "status": "RUNNING", "limit": 20}
)

print(response.json())

const params = new URLSearchParams({ model: 'newton', status: 'RUNNING', limit: '20' });

const response = await fetch(
  `https://api.u1.archetypeai.app/v0.6/fine_tuning/jobs?${params}`,
  {
    headers: {
      'Authorization': `Bearer ${process.env.ATAI_API_KEY}`
    }
  }
);

const data = await response.json();
console.log(data);

{
  "object": "list",
  "data": [
    {
      "object": "fine_tuning.job",
      "id": "your-job-id",
      "name": "my-tune",
      "model": "newton",
      "created_at": 1765201323,
      "org_id": "your-org",
      "status": "RUNNING",
      "checkpoint_id": null,
      "fine_tuned_model": null,
      "finished_at": null,
      "outcome": null,
      "seed": 42,
      "user_provided_suffix": "v2",
      "training_files": ["fil_..."],
      "validation_files": ["fil_..."],
      "errors": []
    }
  ],
  "has_more": false
}

⌘I

​Overview

​Request

​Response

Overview

Request

Response