Resume Reinforcement Fine-tuning Job

POST /v1/accounts/{account_id}/reinforcementFineTuningJobs/{reinforcement_fine_tuning_job_id}:resume

Resume Reinforcement Fine-tuning Job

cURL

curl --request POST \
  --url https://api.fireworks.ai/v1/accounts/{account_id}/reinforcementFineTuningJobs/{reinforcement_fine_tuning_job_id}:resume \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{}'

import requests

url = "https://api.fireworks.ai/v1/accounts/{account_id}/reinforcementFineTuningJobs/{reinforcement_fine_tuning_job_id}:resume"

payload = {}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({})
};

fetch('https://api.fireworks.ai/v1/accounts/{account_id}/reinforcementFineTuningJobs/{reinforcement_fine_tuning_job_id}:resume', 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://api.fireworks.ai/v1/accounts/{account_id}/reinforcementFineTuningJobs/{reinforcement_fine_tuning_job_id}:resume",
  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([
    
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "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://api.fireworks.ai/v1/accounts/{account_id}/reinforcementFineTuningJobs/{reinforcement_fine_tuning_job_id}:resume"

	payload := strings.NewReader("{}")

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

	req.Header.Add("Authorization", "Bearer <token>")
	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://api.fireworks.ai/v1/accounts/{account_id}/reinforcementFineTuningJobs/{reinforcement_fine_tuning_job_id}:resume")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.fireworks.ai/v1/accounts/{account_id}/reinforcementFineTuningJobs/{reinforcement_fine_tuning_job_id}:resume")

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

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{}"

response = http.request(request)
puts response.read_body

200

{
  "dataset": "<string>",
  "evaluator": "<string>",
  "name": "<string>",
  "displayName": "<string>",
  "createTime": "2023-11-07T05:31:56Z",
  "completedTime": "2023-11-07T05:31:56Z",
  "evaluationDataset": "<string>",
  "evalAutoCarveout": true,
  "state": "JOB_STATE_UNSPECIFIED",
  "status": {
    "code": "OK",
    "message": "<string>"
  },
  "createdBy": "<string>",
  "trainingConfig": {
    "outputModel": "<string>",
    "baseModel": "<string>",
    "warmStartFrom": "<string>",
    "jinjaTemplate": "<string>",
    "learningRate": 123,
    "maxContextLength": 123,
    "loraRank": 123,
    "epochs": 123,
    "batchSize": 123,
    "gradientAccumulationSteps": 123,
    "learningRateWarmupSteps": 123,
    "batchSizeSamples": 123,
    "optimizerWeightDecay": 123,
    "trainerShardingScheme": {
      "tensorParallelism": 123,
      "pipelineParallelism": 123,
      "contextParallelism": 123,
      "expertParallelism": 123,
      "sequenceParallelism": true
    },
    "loraAlpha": 123,
    "loraDropout": 123,
    "loraTargetModules": [
      "<string>"
    ]
  },
  "wandbConfig": {
    "enabled": true,
    "apiKey": "<string>",
    "project": "<string>",
    "entity": "<string>",
    "runId": "<string>",
    "url": "<string>"
  },
  "awsS3Config": {
    "credentialsSecret": "<string>",
    "iamRoleArn": "<string>"
  },
  "azureBlobStorageConfig": {
    "credentialsSecret": "<string>",
    "managedIdentityClientId": "<string>",
    "tenantId": "<string>"
  },
  "outputStats": "<string>",
  "jobProgress": {
    "percent": 123,
    "epoch": 123,
    "totalInputRequests": 123,
    "totalProcessedRequests": 123,
    "successfullyProcessedRequests": 123,
    "failedRequests": 123,
    "outputRows": 123,
    "inputTokens": 123,
    "outputTokens": 123,
    "cachedInputTokenCount": 123
  },
  "inferenceParameters": {
    "maxOutputTokens": 123,
    "temperature": 123,
    "topP": 123,
    "responseCandidatesCount": 123,
    "extraBody": "<string>",
    "topK": 123
  },
  "chunkSize": 123,
  "outputMetrics": "<string>",
  "maxInferenceReplicaCount": 123,
  "nodeCount": 123,
  "lossConfig": {
    "method": "METHOD_UNSPECIFIED",
    "klBeta": 123,
    "dpo": {
      "beta": 123,
      "refCacheConcurrency": 123,
      "refCacheBatchSize": 123
    },
    "orpo": {
      "lambda": 123
    }
  },
  "trainerLogsSignedUrl": "<string>",
  "acceleratorSeconds": {},
  "maxConcurrentRollouts": 123,
  "maxConcurrentEvaluations": 123,
  "purpose": "PURPOSE_UNSPECIFIED"
}

Authorizations

Authorization · string · header · required

Bearer authentication using your Fireworks API key. Format: Bearer <API_KEY>

Path Parameters

account_id · string · required

The Account Id

reinforcement_fine_tuning_job_id · string · required

The Reinforcement Fine-tuning Job Id

Body

application/json

The body is of type object.

Response

200 - application/json

A successful response.

dataset · string · required

The name of the dataset used for training.

evaluator · string · required

The evaluator resource name to use for RLOR fine-tuning job.

name · string · read-only

displayName · string

createTime · string<date-time> · read-only

completedTime · string<date-time> · read-only

The completed time for the reinforcement fine-tuning job.

evaluationDataset · string

The name of a separate dataset to use for evaluation.

evalAutoCarveout · boolean

Whether to auto-carve the dataset for eval.

state · enum<string> · default: JOB_STATE_UNSPECIFIED · read-only

JobState represents the state an asynchronous job can be in.

• JOB_STATE_PAUSED: Job is paused, typically due to account suspension or manual intervention.
• JOB_STATE_DELETED: Job has been deleted.

Available options: JOB_STATE_UNSPECIFIED, JOB_STATE_CREATING, JOB_STATE_RUNNING, JOB_STATE_COMPLETED, JOB_STATE_FAILED, JOB_STATE_CANCELLED, JOB_STATE_DELETING, JOB_STATE_WRITING_RESULTS, JOB_STATE_VALIDATING, JOB_STATE_DELETING_CLEANING_UP, JOB_STATE_PENDING, JOB_STATE_EXPIRED, JOB_STATE_RE_QUEUEING, JOB_STATE_CREATING_INPUT_DATASET, JOB_STATE_IDLE, JOB_STATE_CANCELLING, JOB_STATE_EARLY_STOPPED, JOB_STATE_PAUSED, JOB_STATE_DELETED

status · Mimics [https://github.com/googleapis/googleapis/blob/master/google/rpc/status.proto] · object · read-only

Show child attributes

createdBy · string · read-only

The email address of the user who initiated this fine-tuning job.

trainingConfig · BaseTrainingConfig contains common configuration fields shared across different training job types. · object

Common training configurations.

Show child attributes

wandbConfig · object

The Weights & Biases team/user account for logging training progress.

Show child attributes

awsS3Config · object

The AWS configuration for S3 dataset access.

Show child attributes

azureBlobStorageConfig · object

The Azure configuration for Blob Storage dataset access.

Show child attributes

outputStats · string · read-only

The output dataset's aggregated stats for the evaluation job.

jobProgress · object · read-only

Job progress.

Show child attributes

inferenceParameters · RFT inference parameters · object

RFT inference parameters.

Show child attributes

chunkSize · integer<int32>

Data chunking for rollout, default size 200, enabled when dataset > 300. Valid range is 1-10,000.

outputMetrics · string · read-only

maxInferenceReplicaCount · integer<int32>

nodeCount · integer<int32>

The number of nodes to use for the fine-tuning job. If not specified, the default is 1.

lossConfig · object

Reinforcement learning loss method + hyperparameters for the underlying trainers.

Show child attributes

trainerLogsSignedUrl · string · read-only

The signed URL for the trainer logs file (stdout/stderr). Only populated if the account has trainer log reading enabled.

acceleratorSeconds · object · read-only

Accelerator seconds used by the job, keyed by accelerator type (e.g., "NVIDIA_H100_80GB"). Updated when job completes or is cancelled.

Show child attributes

maxConcurrentRollouts · integer<int32>

Maximum number of concurrent rollouts during the RFT job.

maxConcurrentEvaluations · integer<int32>

Maximum number of concurrent evaluations during the RFT job.

purpose · enum<string> · default: PURPOSE_UNSPECIFIED

Scheduling purpose for this job.

Available options: PURPOSE_UNSPECIFIED, PURPOSE_PILOT