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POST
/
v1
/
flow
/
fine-tune
Create fine-tuning job
curl --request POST \
  --url https://flow.seekr.com/v1/flow/fine-tune \
  --header 'Authorization: <api-key>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "training_config": {
    "training_files": [
      "<string>"
    ],
    "model": "<string>",
    "n_epochs": 123,
    "learning_rate": 123,
    "batch_size": 512,
    "n_checkpoints": 123,
    "experiment_name": "<string>",
    "max_length": 2500,
    "pre_train": false,
    "fine_tune_type": "STANDARD",
    "lora_config": {
      "r": 8,
      "alpha": 32,
      "dropout": 0.1,
      "bias": "none",
      "extras": {}
    },
    "reward_components": {
      "graders": [
        {
          "type": "format_check",
          "weight": 0.5
        }
      ],
      "format_reward_weight": 0.1
    },
    "beta": 123,
    "gradient_checkpointing": true
  },
  "infrastructure_config": {
    "n_accel": 123,
    "n_node": 1
  },
  "project_id": 123,
  "description": "<string>"
}
'
import requests

url = "https://flow.seekr.com/v1/flow/fine-tune"

payload = {
    "training_config": {
        "training_files": ["<string>"],
        "model": "<string>",
        "n_epochs": 123,
        "learning_rate": 123,
        "batch_size": 512,
        "n_checkpoints": 123,
        "experiment_name": "<string>",
        "max_length": 2500,
        "pre_train": False,
        "fine_tune_type": "STANDARD",
        "lora_config": {
            "r": 8,
            "alpha": 32,
            "dropout": 0.1,
            "bias": "none",
            "extras": {}
        },
        "reward_components": {
            "graders": [
                {
                    "type": "format_check",
                    "weight": 0.5
                }
            ],
            "format_reward_weight": 0.1
        },
        "beta": 123,
        "gradient_checkpointing": True
    },
    "infrastructure_config": {
        "n_accel": 123,
        "n_node": 1
    },
    "project_id": 123,
    "description": "<string>"
}
headers = {
    "Authorization": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)
const options = {
  method: 'POST',
  headers: {Authorization: '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    training_config: {
      training_files: ['<string>'],
      model: '<string>',
      n_epochs: 123,
      learning_rate: 123,
      batch_size: 512,
      n_checkpoints: 123,
      experiment_name: '<string>',
      max_length: 2500,
      pre_train: false,
      fine_tune_type: 'STANDARD',
      lora_config: {r: 8, alpha: 32, dropout: 0.1, bias: 'none', extras: {}},
      reward_components: {graders: [{type: 'format_check', weight: 0.5}], format_reward_weight: 0.1},
      beta: 123,
      gradient_checkpointing: true
    },
    infrastructure_config: {n_accel: 123, n_node: 1},
    project_id: 123,
    description: '<string>'
  })
};

fetch('https://flow.seekr.com/v1/flow/fine-tune', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));
<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://flow.seekr.com/v1/flow/fine-tune",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'training_config' => [
        'training_files' => [
                '<string>'
        ],
        'model' => '<string>',
        'n_epochs' => 123,
        'learning_rate' => 123,
        'batch_size' => 512,
        'n_checkpoints' => 123,
        'experiment_name' => '<string>',
        'max_length' => 2500,
        'pre_train' => false,
        'fine_tune_type' => 'STANDARD',
        'lora_config' => [
                'r' => 8,
                'alpha' => 32,
                'dropout' => 0.1,
                'bias' => 'none',
                'extras' => [
                                
                ]
        ],
        'reward_components' => [
                'graders' => [
                                [
                                                                'type' => 'format_check',
                                                                'weight' => 0.5
                                ]
                ],
                'format_reward_weight' => 0.1
        ],
        'beta' => 123,
        'gradient_checkpointing' => true
    ],
    'infrastructure_config' => [
        'n_accel' => 123,
        'n_node' => 1
    ],
    'project_id' => 123,
    'description' => '<string>'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: <api-key>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}
package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://flow.seekr.com/v1/flow/fine-tune"

	payload := strings.NewReader("{\n  \"training_config\": {\n    \"training_files\": [\n      \"<string>\"\n    ],\n    \"model\": \"<string>\",\n    \"n_epochs\": 123,\n    \"learning_rate\": 123,\n    \"batch_size\": 512,\n    \"n_checkpoints\": 123,\n    \"experiment_name\": \"<string>\",\n    \"max_length\": 2500,\n    \"pre_train\": false,\n    \"fine_tune_type\": \"STANDARD\",\n    \"lora_config\": {\n      \"r\": 8,\n      \"alpha\": 32,\n      \"dropout\": 0.1,\n      \"bias\": \"none\",\n      \"extras\": {}\n    },\n    \"reward_components\": {\n      \"graders\": [\n        {\n          \"type\": \"format_check\",\n          \"weight\": 0.5\n        }\n      ],\n      \"format_reward_weight\": 0.1\n    },\n    \"beta\": 123,\n    \"gradient_checkpointing\": true\n  },\n  \"infrastructure_config\": {\n    \"n_accel\": 123,\n    \"n_node\": 1\n  },\n  \"project_id\": 123,\n  \"description\": \"<string>\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}
HttpResponse<String> response = Unirest.post("https://flow.seekr.com/v1/flow/fine-tune")
  .header("Authorization", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"training_config\": {\n    \"training_files\": [\n      \"<string>\"\n    ],\n    \"model\": \"<string>\",\n    \"n_epochs\": 123,\n    \"learning_rate\": 123,\n    \"batch_size\": 512,\n    \"n_checkpoints\": 123,\n    \"experiment_name\": \"<string>\",\n    \"max_length\": 2500,\n    \"pre_train\": false,\n    \"fine_tune_type\": \"STANDARD\",\n    \"lora_config\": {\n      \"r\": 8,\n      \"alpha\": 32,\n      \"dropout\": 0.1,\n      \"bias\": \"none\",\n      \"extras\": {}\n    },\n    \"reward_components\": {\n      \"graders\": [\n        {\n          \"type\": \"format_check\",\n          \"weight\": 0.5\n        }\n      ],\n      \"format_reward_weight\": 0.1\n    },\n    \"beta\": 123,\n    \"gradient_checkpointing\": true\n  },\n  \"infrastructure_config\": {\n    \"n_accel\": 123,\n    \"n_node\": 1\n  },\n  \"project_id\": 123,\n  \"description\": \"<string>\"\n}")
  .asString();
require 'uri'
require 'net/http'

url = URI("https://flow.seekr.com/v1/flow/fine-tune")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"training_config\": {\n    \"training_files\": [\n      \"<string>\"\n    ],\n    \"model\": \"<string>\",\n    \"n_epochs\": 123,\n    \"learning_rate\": 123,\n    \"batch_size\": 512,\n    \"n_checkpoints\": 123,\n    \"experiment_name\": \"<string>\",\n    \"max_length\": 2500,\n    \"pre_train\": false,\n    \"fine_tune_type\": \"STANDARD\",\n    \"lora_config\": {\n      \"r\": 8,\n      \"alpha\": 32,\n      \"dropout\": 0.1,\n      \"bias\": \"none\",\n      \"extras\": {}\n    },\n    \"reward_components\": {\n      \"graders\": [\n        {\n          \"type\": \"format_check\",\n          \"weight\": 0.5\n        }\n      ],\n      \"format_reward_weight\": 0.1\n    },\n    \"beta\": 123,\n    \"gradient_checkpointing\": true\n  },\n  \"infrastructure_config\": {\n    \"n_accel\": 123,\n    \"n_node\": 1\n  },\n  \"project_id\": 123,\n  \"description\": \"<string>\"\n}"

response = http.request(request)
puts response.read_body
{}
{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}
Create a fine-tuning job by specifying a TrainingConfig and InfrastructureConfig. The TrainingConfig accepts an optional lora_config parameter for parameter-efficient training using low-rank adaptation. For guidance on configuring LoRA, see Low-rank adaptation. For the full fine-tuning workflow, see Create a fine-tuning job.

Authorizations

​
Authorization
string
header
required

Your Seekr API key, sent in the Authorization header with no 'Bearer' prefix.

Body

application/json
​
training_config
TrainingConfig · object
required
​
infrastructure_config
InfrastructureConfig · object
required
​
project_id
integer | null
​
description
string | null

Response

Successful Response

The response is of type object.

Last modified on June 18, 2026