> ## Documentation Index > Fetch the complete documentation index at: https://docs.platform.toloka.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Get a training > Return the training metadata and saved configuration, including applied defaults and dataset selections. ## OpenAPI ````yaml /api-reference/openapi.json get /trainings/{trainingId} openapi: 3.1.0 info: description: >- Manage projects, datasets, labeling pipelines, and model training. **Beta:** endpoints, request and response shapes, and error contracts can change without notice or a backward-compatibility promise. title: Toloka Platform API version: 2.0.0 servers: - url: https://platform.toloka.ai/api/v2-beta security: - apiKeyAuth: [] - scopedTokenAuth: [] tags: - description: The authenticated API key owner. name: Account - description: A project is the container for pipelines, datasets, and files. name: Projects - description: Rows and typed fields. Field schemas are immutable once created. name: Datasets - description: Append rows to a dataset from a file. name: Dataset uploads - description: Read a dataset out as a file. name: Dataset exports - description: A pipeline is a graph of nodes that processes each dataset item. name: Pipelines - description: The nodes, connections, fields, and version of a pipeline graph. name: Pipeline graph - description: Execute a pipeline over a dataset and inspect each item. name: Runs - description: Per-node checks that a pipeline must pass before deployment. name: Checks - description: Named credentials available to pipeline code. name: Secrets - description: Project files available to pipeline code and labeling interfaces. name: Files - description: >- Global, read-only catalog of the models a synthetic generation node can use, with their budget bounds. name: Generation models - description: >- Global, read-only catalog of the expert audience: the values a node `audience` filter can use. name: Audience - description: >- Project lists of experts a node can take its workforce from with `audienceMode: service`. Available only to teams with the audience service enabled. name: Expert lists - description: >- Experts banned in a project: they cannot be invited and are removed from the work they are in. Available only to teams with expert bans enabled. name: Expert ban list - description: Global, read-only base model catalog. name: Base models - description: Project-owned mutable model-training drafts. name: Trainings - description: Project-owned Models and immutable Model Versions. name: Models - name: Batch inference paths: /trainings/{trainingId}: get: tags: - Trainings summary: Get a training description: >- Return the training metadata and saved configuration, including applied defaults and dataset selections. operationId: getTraining parameters: - in: path name: trainingId required: true schema: $ref: '#/components/schemas/TrainingId' responses: '200': content: application/json: schema: $ref: '#/components/schemas/Training' description: Training draft headers: RateLimit-Limit: $ref: '#/components/headers/RateLimit-Limit' RateLimit-Policy: $ref: '#/components/headers/RateLimit-Policy' RateLimit-Remaining: $ref: '#/components/headers/RateLimit-Remaining' RateLimit-Reset: $ref: '#/components/headers/RateLimit-Reset' X-Request-Id: $ref: '#/components/headers/X-Request-Id' '404': description: Training not found headers: RateLimit-Limit: $ref: '#/components/headers/RateLimit-Limit' RateLimit-Policy: $ref: '#/components/headers/RateLimit-Policy' RateLimit-Remaining: $ref: '#/components/headers/RateLimit-Remaining' RateLimit-Reset: $ref: '#/components/headers/RateLimit-Reset' X-Request-Id: $ref: '#/components/headers/X-Request-Id' '429': description: Rate limit exceeded headers: RateLimit-Limit: $ref: '#/components/headers/RateLimit-Limit' RateLimit-Policy: $ref: '#/components/headers/RateLimit-Policy' RateLimit-Remaining: $ref: '#/components/headers/RateLimit-Remaining' RateLimit-Reset: $ref: '#/components/headers/RateLimit-Reset' X-Request-Id: $ref: '#/components/headers/X-Request-Id' x-codeSamples: - label: TypeScript SDK lang: typescript source: | import { createClient } from "@toloka-platform/sdk"; const client = createClient({ baseUrl: "https://platform.toloka.ai", apiKey: process.env.TOLOKA_API_KEY!, }); const training = await client.trainings.get({ trainingId: "trg.019a0000-0000-7000-8000-000000000001" }); console.log(training); components: schemas: TrainingId: description: Training draft ID with prefix `trg.`. pattern: >- ^trg\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string Training: description: >- A project-owned mutable Training draft. The output Model is bound on the first Training Run. properties: archivedAt: anyOf: - format: date-time pattern: >- ^(?:(?:\d\d[2468][048]|\d\d[13579][26]|\d\d0[48]|[02468][048]00|[13579][26]00)-02-29|\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\d|30)|(?:02)-(?:0[1-9]|1\d|2[0-8])))T(?:(?:[01]\d|2[0-3]):[0-5]\d:[0-5]\d(?:\.\d+)?(?:Z))$ type: string - type: 'null' description: >- Time the training was archived, as an ISO 8601 timestamp, or null while it is active. configuration: $ref: '#/components/schemas/TrainingConfiguration' createdAt: description: Time the training was created, as an ISO 8601 timestamp. format: date-time pattern: >- ^(?:(?:\d\d[2468][048]|\d\d[13579][26]|\d\d0[48]|[02468][048]00|[13579][26]00)-02-29|\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\d|30)|(?:02)-(?:0[1-9]|1\d|2[0-8])))T(?:(?:[01]\d|2[0-3]):[0-5]\d:[0-5]\d(?:\.\d+)?(?:Z))$ type: string id: $ref: '#/components/schemas/TrainingId' modelId: anyOf: - $ref: '#/components/schemas/ModelId' - type: 'null' description: >- Output model ID with prefix `mdl.`, or null before the first training run. name: description: Name of the training draft. type: string projectId: $ref: '#/components/schemas/ProjectId' updatedAt: description: Time the training was last updated, as an ISO 8601 timestamp. format: date-time pattern: >- ^(?:(?:\d\d[2468][048]|\d\d[13579][26]|\d\d0[48]|[02468][048]00|[13579][26]00)-02-29|\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\d|30)|(?:02)-(?:0[1-9]|1\d|2[0-8])))T(?:(?:[01]\d|2[0-3]):[0-5]\d:[0-5]\d(?:\.\d+)?(?:Z))$ type: string required: - id - projectId - modelId - name - configuration - archivedAt - createdAt - updatedAt type: object TrainingConfiguration: description: A normalized method-specific Training draft. oneOf: - $ref: '#/components/schemas/SftTrainingConfiguration' - $ref: '#/components/schemas/GistingTrainingConfiguration' ModelId: description: Model ID with prefix `mdl.`. pattern: >- ^mdl\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string ProjectId: description: Project ID with prefix `pp.`. pattern: >- ^pp\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string SftTrainingConfiguration: additionalProperties: false description: A normalized supervised fine-tuning draft using LoRA. properties: batchSize: description: >- Sequences per optimizer step across all GPUs: 8, 16, 32, or 64. The default is 8. enum: - 8 - 16 - 32 - 64 type: number epochs: description: >- Passes over the training selection, 1 through 5. The cost estimate grows linearly with epochs. maximum: 5 minimum: 1 type: integer learningRate: description: >- Optimizer learning rate, 0.00001 through 0.001. The default is 0.00015. maximum: 0.001 minimum: 0.00001 type: number loraRank: description: >- LoRA adapter rank: 8, 16, or 32. Defaults to 16. Alpha is twice the rank. enum: - 8 - 16 - 32 type: number maxSequenceLength: description: >- Token budget per training example, prompt and target together: 64 through 16384. The cost estimate is blocked when the longest example exceeds it. Defaults: 12288 for SFT, 3072 for gisting. maximum: 16384 minimum: 64 type: integer method: const: sft description: >- Training method; `sft` learns a LoRA adapter from prompt and target examples. type: string sliceId: description: >- The dataset slice to train on. It must freeze a split field. Training uses its train parts and validation uses its validate parts at the slice cutoff. Rows marked as test by any split field are excluded, except validation rows in a part with both validate and test roles in the selected split field. pattern: >- ^dsl\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string source: $ref: '#/components/schemas/TrainingModelSource' splitFieldId: description: >- The split field to use, identified by field ID. Required when the slice freezes more than one split field. pattern: >- ^df\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string trainParts: description: >- The train parts to learn on. Defaults to every part with the train role. items: maxLength: 64 pattern: ^[A-Za-z0-9_]+(?:[.-][A-Za-z0-9_]+)*$ type: string maxItems: 10 minItems: 1 type: array training: $ref: '#/components/schemas/TrainingDatasetSelection' validation: $ref: '#/components/schemas/TrainingDatasetSelection' required: - method - source - loraRank - epochs - learningRate - batchSize - maxSequenceLength - training type: object GistingTrainingConfiguration: additionalProperties: false description: A normalized prompt-gisting Training draft. properties: batchSize: description: >- Sequences per optimizer step across all GPUs: 8, 16, 32, or 64. The default is 8. enum: - 8 - 16 - 32 - 64 type: number epochs: description: >- Passes over the training selection, 1 through 5. The cost estimate grows linearly with epochs. maximum: 5 minimum: 1 type: integer gistTokens: description: >- Number of learned tokens that replace the prompt: 8, 32, 64, or a fraction of the prompt length: "1/4", "1/8", "1/16", or "1/32". Fractions are rounded up to a whole token and limited to 8 through 256 tokens. Defaults to "1/8". enum: - 8 - 32 - 64 - 1/4 - 1/8 - 1/16 - 1/32 learningRate: description: >- Optimizer learning rate for the soft tokens, 0.001 through 0.3. The default is 0.03. maximum: 0.3 minimum: 0.001 type: number maxSequenceLength: description: >- Token budget per training example, prompt and target together: 64 through 16384. The cost estimate is blocked when the longest example exceeds it. Defaults: 12288 for SFT, 3072 for gisting. maximum: 16384 minimum: 64 type: integer method: const: gisting description: >- Training method; `gisting` learns tokens that replace a reusable prompt. type: string promptFileId: description: >- Project file ID with prefix `ppf.` containing the finalized UTF-8 prompt to compress. pattern: >- ^ppf\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string sliceId: description: >- The dataset slice to train on. It must freeze a split field. Training uses its train parts and validation uses its validate parts at the slice cutoff. Rows marked as test by any split field are excluded, except validation rows in a part with both validate and test roles in the selected split field. pattern: >- ^dsl\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string source: $ref: '#/components/schemas/TrainingModelSource' splitFieldId: description: >- The split field to use, identified by field ID. Required when the slice freezes more than one split field. pattern: >- ^df\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string trainParts: description: >- The train parts to learn on. Defaults to every part with the train role. items: maxLength: 64 pattern: ^[A-Za-z0-9_]+(?:[.-][A-Za-z0-9_]+)*$ type: string maxItems: 10 minItems: 1 type: array training: $ref: '#/components/schemas/TrainingDatasetSelection' validation: $ref: '#/components/schemas/TrainingDatasetSelection' required: - method - source - promptFileId - gistTokens - epochs - learningRate - batchSize - maxSequenceLength - training type: object TrainingModelSource: description: The exact Base Model or Model Version used as the source. oneOf: - additionalProperties: false properties: baseModelId: description: Catalog base model identifier. enum: - qwen3-4b - qwen3-8b - qwen3-32b - qwen3-235b type: string type: const: base_model description: >- Training source: `base_model` uses a catalog model; `model_version` uses a published project model version. type: string required: - type - baseModelId type: object - additionalProperties: false properties: modelVersionId: description: Source model version ID with prefix `mdv.`. pattern: >- ^mdv\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string type: const: model_version description: >- Training source: `base_model` uses a catalog model; `model_version` uses a published project model version. type: string required: - type - modelVersionId type: object TrainingDatasetSelection: additionalProperties: false description: A Dataset and normalized filter selected for one Training input purpose. properties: datasetId: description: Dataset ID with prefix `ds.` containing the selected examples. pattern: >- ^ds\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string itemFilter: $ref: '#/components/schemas/TrainingDatasetItemFilter' description: >- Conditions selecting dataset rows; omitted conditions do not restrict the selection. required: - datasetId - itemFilter type: object TrainingDatasetItemFilter: additionalProperties: false description: A normalized Dataset item filter stored with a Training draft. properties: excludeParts: $ref: '#/components/schemas/DatasetSplitPartExclusions' fieldSources: $ref: '#/components/schemas/DatasetFieldSourceConditions' fieldValues: $ref: '#/components/schemas/DatasetFieldValueConditions' missingRevisionFields: description: >- Field IDs with prefix `df.` that must have no revision on a selected row; defaults to an empty array. items: pattern: >- ^df\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string type: array parts: $ref: '#/components/schemas/DatasetSplitPartInclusion' slice: $ref: '#/components/schemas/DatasetSliceSelection' required: - fieldValues - fieldSources - missingRevisionFields type: object DatasetSplitPartExclusions: description: Split-part selections to exclude; omit when no parts should be excluded. items: additionalProperties: false description: Split field and selected part names. properties: fieldId: description: Split field ID with prefix `df.`. pattern: >- ^df\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string names: description: Names of the split parts to select. items: maxLength: 64 pattern: ^[A-Za-z0-9_]+(?:[.-][A-Za-z0-9_]+)*$ type: string maxItems: 10 minItems: 1 type: array required: - fieldId - names type: object maxItems: 500 type: array DatasetFieldSourceConditions: description: >- Field-author conditions that selected rows must satisfy; defaults to no conditions. items: additionalProperties: false description: Required authors for a field. properties: fieldId: description: Dataset field ID with prefix `df.`. pattern: >- ^df\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string sources: description: Revision authors to match for this field. items: $ref: '#/components/schemas/FieldRevisionSource' minItems: 1 type: array required: - fieldId - sources type: object type: array DatasetFieldValueConditions: description: >- Field-value conditions that selected rows must satisfy; defaults to no conditions. items: additionalProperties: false description: Condition applied to a field value. properties: fieldId: description: Dataset field ID with prefix `df.` to compare. pattern: >- ^df\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string jsonPath: description: JSONPath locating the value within the field. minLength: 1 type: string latestOnly: default: true description: >- Whether to test only the latest revision from the allowed authors; false tests any revision, and the default is true. type: boolean operator: description: >- Text comparison: `text_eq` for equality or `text_neq` for inequality. enum: - text_eq - text_neq type: string sources: default: [] description: Allowed revision authors; an empty array allows any author. items: $ref: '#/components/schemas/FieldRevisionSource' type: array value: description: Scalar value compared as text; null is treated as an empty string. type: - string - number - boolean - 'null' required: - jsonPath - operator - value - fieldId type: object type: array DatasetSplitPartInclusion: additionalProperties: false description: Split parts to include; omit to include every part. properties: fieldId: description: Split field ID with prefix `df.`. pattern: >- ^df\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string names: description: Names of the split parts to select. items: maxLength: 64 pattern: ^[A-Za-z0-9_]+(?:[.-][A-Za-z0-9_]+)*$ type: string maxItems: 10 minItems: 1 type: array required: - fieldId - names type: object DatasetSliceSelection: additionalProperties: false description: >- Slice whose frozen rows and fields to read; omit to use live dataset rows. properties: sliceId: description: Dataset slice ID with prefix `dsl.`. pattern: >- ^dsl\.[0-9a-f]{8}-[0-9a-f]{4}-[7][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$ type: string required: - sliceId type: object FieldRevisionSource: description: Source that wrote a field revision. oneOf: - additionalProperties: false description: Source that wrote a field revision. properties: type: const: user description: >- Revision author: `user` for a user action or `system` for a platform operation. type: string userId: description: Identifier of the user who wrote the revision. minLength: 1 type: string required: - type - userId type: object - additionalProperties: false description: Source that wrote a field revision. properties: source: description: Identifier of the platform operation that wrote the revision. minLength: 1 type: string type: const: system description: >- Revision author: `user` for a user action or `system` for a platform operation. type: string required: - type - source type: object headers: RateLimit-Limit: description: The maximum number of requests allowed in the current window. schema: type: integer RateLimit-Policy: description: The rate limit policy (e.g., "60;w=60"). schema: type: string RateLimit-Remaining: description: The number of requests remaining in the current window. schema: type: integer RateLimit-Reset: description: The number of seconds until the current window resets. schema: type: integer X-Request-Id: description: >- The request id: the X-Request-Id you sent when it is 1-128 characters of letters, digits, ".", "_" or "-", otherwise a generated UUID. Present on every response, including errors; quote it when reporting a problem. schema: type: string securitySchemes: apiKeyAuth: description: >- Enter `ApiKey ` in Authorization, including the `ApiKey ` prefix. In cURL and Python samples, `` means this full value. The TypeScript SDK adds the prefix for you. in: header name: Authorization type: apiKey scopedTokenAuth: description: >- Enter the project-scoped token as `pst_...` in X-Scoped-Token, without an `ApiKey ` prefix. Create a token with POST /projects/{projectId}/tokens. in: header name: X-Scoped-Token type: apiKey ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.