> ## Documentation Index > Fetch the complete documentation index at: https://docs.compute.prentis.ai/llms.txt > Use this file to discover all available pages before exploring further. # Estimate a supervised fine-tuning job > What the same request to create would cost, and whether it would be allowed to run -- without creating anything. The estimate shows its working (examples, tokens per example, epochs, rate) so you can tell whether the number is for the job you meant. An estimate is not the bill: you are billed for the tokens actually trained on. ## OpenAPI ````yaml openapi/prentis-training.openapi.yaml POST /accounts/{account}/supervisedFineTuningJobs:estimateCost openapi: 3.1.0 info: title: Prentis Training API version: 0.1.0 summary: >- Fine-tune models on your own data, with the same API key you use for inference. description: > Upload a dataset, start a fine-tuning job on it, and watch it train -- from code, with the API key you already use for inference. The jobs and datasets are the same ones the console shows: anything started here appears there, and the other way round. Every path is under `/v1/accounts/{account}`, where `{account}` is the account the key belongs to. A key reaches its own account only. A finished job produces a model in your account (`accounts/{account}/models/{outputModelId}`), listed under Custom models in the console. To call it, deploy it on a dedicated deployment and send inference requests to the deployment (`accounts/{account}/deployments/{deployment}`). servers: - url: https://compute.prentis.ai/v1 description: Production security: - bearerAuth: [] tags: - name: training - name: datasets paths: /accounts/{account}/supervisedFineTuningJobs:estimateCost: post: tags: - training summary: Estimate a supervised fine-tuning job description: >- What the same request to create would cost, and whether it would be allowed to run -- without creating anything. The estimate shows its working (examples, tokens per example, epochs, rate) so you can tell whether the number is for the job you meant. An estimate is not the bill: you are billed for the tokens actually trained on. operationId: estimateSupervisedFineTuningJobCost parameters: - $ref: '#/components/parameters/Account' requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/TrainingJobDraft' responses: '200': headers: x-request-id: $ref: '#/components/headers/x-request-id' content: application/json: schema: $ref: '#/components/schemas/EstimateCostResponse' example: estimate: exampleCount: '4000' avgTokensPerExample: '535' epochs: 2 tokensProcessed: '4280000' ratePerMillion: amount: '0.45' currency: USD estimatedCost: amount: '1.93' currency: USD egress: allowed: true execution: thirdParty: false providerApproved: true requiredAgreementVersion: v2 acceptedAgreementVersion: v2 description: OK. '400': $ref: '#/components/responses/Error400' '401': $ref: '#/components/responses/Error401' '403': $ref: '#/components/responses/Error403' '404': $ref: '#/components/responses/Error404' '500': $ref: '#/components/responses/Error500' '503': $ref: '#/components/responses/Error503' x-codeSamples: - lang: curl label: cURL source: >- curl https://compute.prentis.ai/v1/accounts/my-account/supervisedFineTuningJobs:estimateCost \ -H "Authorization: Bearer $PRENTIS_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "baseModel": "accounts/maas/models/your-base-model", "inputDatasetVersion": "accounts/my-account/datasets/support-chats", "config": { "outputModelId": "support-lora-v1", "epochs": 2 } }' components: parameters: Account: name: account in: path required: true schema: type: string maxLength: 64 description: >- Your account id -- the one in the console's address bar (my-account for this key). It must be the account the key belongs to. schemas: TrainingJobDraft: type: object required: - baseModel - inputDatasetVersion - config properties: baseModel: type: string maxLength: 256 description: >- The model to fine-tune, as a full resource name (accounts/maas/models/your-base-model). Only base models offered for training are accepted -- the console's Training page lists them. The model to fine-tune, as a full resource name (accounts/maas/models/your-base-model). Only base models offered for training are accepted -- the console's Training page lists them. The model to fine-tune, as a full resource name (accounts/maas/models/your-base-model). Only base models offered for training are accepted -- the console's Training page lists them. The model to fine-tune, as a full resource name (accounts/maas/models/your-base-model). Only base models offered for training are accepted -- the console's Training page lists them. inputDatasetVersion: type: string maxLength: 256 description: >- The training data: a dataset (accounts/{account}/datasets/{dataset}) to use its latest version, or one version (…/versions/{n}) to pin it. The dataset must be READY. The preference data: a dataset to use its latest version, or one version to pin it. Each row needs a prompt and two answers -- see the dataset format guide. The dataset must be READY. The training data: a dataset (accounts/{account}/datasets/{dataset}) to use its latest version, or one version (…/versions/{n}) to pin it. The dataset must be READY. The training data: a dataset (accounts/{account}/datasets/{dataset}) to use its latest version, or one version (…/versions/{n}) to pin it. The dataset must be READY. evaluationDatasetVersion: type: string maxLength: 256 description: >- Accepted so that the body of a create can be sent unchanged, but not used: the estimate covers the training data only. Optional held-out data to measure evaluation loss on, in the same form as inputDatasetVersion. Leave it empty and set config.evalAutoCarveoutBasisPoints to hold out a share of the training data instead, or leave both empty for no evaluation. Accepted so that the body of a create can be sent unchanged, but not used: the estimate covers the training data only. Optional held-out data to measure evaluation loss on, in the same form as inputDatasetVersion. Leave it empty and set config.evalAutoCarveoutBasisPoints to hold out a share of the training data instead, or leave both empty for no evaluation. config: $ref: '#/components/schemas/TrainingConfig' description: >- How to train. outputModelId is required: the id of the model the job will create, which must not already exist in your account. The rest are optional -- loraRank, learningRate (a string, e.g. "1e-4"), epochs (1-100), batchSize, maxContextLength (longer examples are skipped and counted, never truncated), earlyStop, evalAutoCarveoutBasisPoints (0-9999, in hundredths of a percent), lrSchedule (constant, cosine or linear_decay), warmupSteps, and dpoBeta (preference jobs only; a string, default "0.1"). Fixed once the job is created. How to train. outputModelId is required: the id of the model the job will create, which must not already exist in your account. The rest are optional -- loraRank, learningRate (a string, e.g. "1e-4"), epochs (1-100), batchSize, maxContextLength (longer examples are skipped and counted, never truncated), earlyStop, evalAutoCarveoutBasisPoints (0-9999, in hundredths of a percent), lrSchedule (constant, cosine or linear_decay), warmupSteps, and dpoBeta (preference jobs only; a string, default "0.1"). Fixed once the job is created. How to train. outputModelId is required: the id of the model the job will create, which must not already exist in your account. The rest are optional -- loraRank, learningRate (a string, e.g. "1e-4"), epochs (1-100), batchSize, maxContextLength (longer examples are skipped and counted, never truncated), earlyStop, evalAutoCarveoutBasisPoints (0-9999, in hundredths of a percent), lrSchedule (constant, cosine or linear_decay), warmupSteps, and dpoBeta (preference jobs only; a string, default "0.1"). Fixed once the job is created. How to train. outputModelId is required: the id of the model the job will create, which must not already exist in your account. The rest are optional -- loraRank, learningRate (a string, e.g. "1e-4"), epochs (1-100), batchSize, maxContextLength (longer examples are skipped and counted, never truncated), earlyStop, evalAutoCarveoutBasisPoints (0-9999, in hundredths of a percent), lrSchedule (constant, cosine or linear_decay), warmupSteps, and dpoBeta (preference jobs only; a string, default "0.1"). Fixed once the job is created. EstimateCostResponse: type: object properties: estimate: $ref: '#/components/schemas/TrainingEstimate' egress: $ref: '#/components/schemas/TrainingEgress' TrainingConfig: type: object required: - outputModelId properties: outputModelId: type: string maxLength: 64 loraRank: type: integer learningRate: type: string epochs: type: integer batchSize: type: integer maxContextLength: type: integer earlyStop: type: boolean evalAutoCarveoutBasisPoints: type: integer minimum: 0 maximum: 9999 lrSchedule: type: string warmupSteps: type: integer dpoBeta: type: string TrainingEstimate: type: object properties: exampleCount: type: string format: int64 avgTokensPerExample: type: string format: int64 epochs: type: integer tokensProcessed: type: string format: int64 ratePerMillion: allOf: - $ref: '#/components/schemas/Money' estimatedCost: $ref: '#/components/schemas/Money' rateMissing: type: boolean TrainingEgress: type: object properties: allowed: type: boolean refusalCode: type: string enum: - DATA_RESIDENCY_VIOLATION - AGREEMENT_REQUIRED - PROVIDER_NOT_ALLOWED - PROVIDER_SERVICE_UNAVAILABLE execution: $ref: '#/components/schemas/JobExecution' providerApproved: type: boolean requiredAgreementVersion: type: string acceptedAgreementVersion: type: string organizationResidency: type: string ErrorResponse: type: object required: - error properties: error: type: object required: - message - type - code properties: message: type: string type: type: string enum: - invalid_request_error - authentication_error - permission_error - not_found_error - rate_limit_error - server_error - service_unavailable - billing_error code: type: string enum: - INVALID_REQUEST - INVALID_API_KEY - OPERATION_NOT_ALLOWED - TENANT_SUSPENDED - AGREEMENT_REQUIRED - DATA_RESIDENCY_VIOLATION - PROVIDER_NOT_ALLOWED - PROVIDER_SERVICE_UNAVAILABLE - INSUFFICIENT_BALANCE - PAYMENT_REQUIRED - MODEL_NOT_FOUND - MODEL_ALREADY_EXISTS - DATASET_NOT_FOUND - DATASET_ALREADY_EXISTS - DATASET_STATE_INVALID - DATASET_IN_USE - DATASET_TOO_LARGE - JSONL_LINE_NOT_OBJECT - JSONL_MISSING_FIELD - JSONL_ENCODING - JOB_NOT_FOUND - JOB_STATE_INVALID - TRAINING_RUN_ABANDONED - TRAINING_TOKENIZE_FAILED - TRAINING_BASE_NOT_EXPORTABLE - IDEMPOTENCY_CONFLICT - QUOTA_EXCEEDED - INTERNAL - STORAGE_UNAVAILABLE param: type: - string - 'null' Money: type: object properties: amount: type: string currency: type: string JobExecution: type: object properties: providerDisplayName: type: string thirdParty: type: boolean headers: x-request-id: schema: type: string required: true description: >- On every response, successes and errors alike. Quote it when you ask us about a call. Retry-After: schema: type: integer minimum: 0 description: How many seconds to wait before retrying, on the responses that set it. responses: Error400: headers: x-request-id: $ref: '#/components/headers/x-request-id' content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' description: >- `error.code` is one of: `DATASET_STATE_INVALID`, `INVALID_REQUEST`, `JSONL_ENCODING`, `JSONL_LINE_NOT_OBJECT`, `JSONL_MISSING_FIELD`, `TRAINING_BASE_NOT_EXPORTABLE`, `TRAINING_TOKENIZE_FAILED`. See the Errors page for what each one means, whether it is safe to retry, and whether it is billed. Error401: headers: x-request-id: $ref: '#/components/headers/x-request-id' content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' description: >- `error.code` is one of: `INVALID_API_KEY`. See the Errors page for what each one means, whether it is safe to retry, and whether it is billed. Error403: headers: x-request-id: $ref: '#/components/headers/x-request-id' content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' description: >- `error.code` is one of: `AGREEMENT_REQUIRED`, `DATA_RESIDENCY_VIOLATION`, `OPERATION_NOT_ALLOWED`, `PROVIDER_NOT_ALLOWED`, `PROVIDER_SERVICE_UNAVAILABLE`, `TENANT_SUSPENDED`. See the Errors page for what each one means, whether it is safe to retry, and whether it is billed. Error404: headers: x-request-id: $ref: '#/components/headers/x-request-id' content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' description: >- `error.code` is one of: `DATASET_NOT_FOUND`, `JOB_NOT_FOUND`, `MODEL_NOT_FOUND`. See the Errors page for what each one means, whether it is safe to retry, and whether it is billed. Error500: headers: x-request-id: $ref: '#/components/headers/x-request-id' content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' description: >- `error.code` is one of: `INTERNAL`, `TRAINING_RUN_ABANDONED`. See the Errors page for what each one means, whether it is safe to retry, and whether it is billed. Error503: headers: x-request-id: $ref: '#/components/headers/x-request-id' Retry-After: $ref: '#/components/headers/Retry-After' content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' description: >- `error.code` is one of: `STORAGE_UNAVAILABLE`. See the Errors page for what each one means, whether it is safe to retry, and whether it is billed. securitySchemes: bearerAuth: type: http scheme: bearer description: >- `Authorization: Bearer ` -- the same key as inference. A key reaches the account it belongs to and no other. ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.