For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
DASHBOARDPLAYGROUNDDOCSCOMMUNITYLOG IN
Guides and conceptsAPI ReferenceRelease NotesLLMUCookbooks
Guides and conceptsAPI ReferenceRelease NotesLLMUCookbooks
  • Cohere API
    • About
    • Teams and Roles
    • Errors
    • Migrating From API v1 to API v2
    • Using the OpenAI SDK
  • Endpoints
  • Deprecated
      • GETLists fine-tuned models.
      • POSTTrains and deploys a fine-tuned model.
      • PATCHUpdates a fine-tuned model.
      • GETReturns a fine-tuned model by ID.
      • DELDeletes a fine-tuned model.
      • GETFetch history of statuses for a fine-tuned model.
      • GETRetrieve training metrics for fine-tuned models.
LogoLogodocs
DASHBOARDPLAYGROUNDDOCSCOMMUNITYLOG IN
Deprecatedv1/finetuning

Updates a fine-tuned model.

Deprecated
PATCH
https://api.cohere.com/v1/finetuning/finetuned-models/:id
PATCH
/v1/finetuning/finetuned-models/:id
1from cohere.finetuning import (
2    BaseModel,
3    Settings,
4)
5import cohere
6
7co = cohere.Client()
8finetuned_model = co.finetuning.update_finetuned_model(
9    id="test-id",
10    name="new name",
11    settings=Settings(
12        base_model=BaseModel(
13            base_type="BASE_TYPE_CHAT",
14        ),
15        dataset_id="my-dataset-id",
16    ),
17)
18
19print(finetuned_model)
1{
2  "finetuned_model": {
3    "name": "string",
4    "settings": {
5      "base_model": {
6        "base_type": "BASE_TYPE_UNSPECIFIED",
7        "name": "string",
8        "version": "string",
9        "strategy": "STRATEGY_UNSPECIFIED"
10      },
11      "dataset_id": "string",
12      "hyperparameters": {
13        "early_stopping_patience": 1,
14        "early_stopping_threshold": 1.1,
15        "train_batch_size": 1,
16        "train_epochs": 1,
17        "learning_rate": 1.1,
18        "lora_alpha": 1,
19        "lora_rank": 1,
20        "lora_target_modules": "LORA_TARGET_MODULES_UNSPECIFIED"
21      },
22      "multi_label": true,
23      "wandb": {
24        "project": "string",
25        "api_key": "string",
26        "entity": "string"
27      }
28    },
29    "id": "string",
30    "creator_id": "string",
31    "organization_id": "string",
32    "status": "STATUS_UNSPECIFIED",
33    "created_at": "2024-01-15T09:30:00Z",
34    "updated_at": "2024-01-15T09:30:00Z",
35    "completed_at": "2024-01-15T09:30:00Z",
36    "last_used": "2024-01-15T09:30:00Z"
37  }
38}

Updates the fine-tuned model with the given ID. The model will be updated with the new settings and name provided in the request body.

Was this page helpful?
Previous

Returns a fine-tuned model by ID.

Next
Built with

Authentication

AuthorizationBearer

Bearer authentication of the form Bearer <token>, where token is your auth token.

Path parameters

idstringRequired
FinetunedModel ID.

Headers

X-Client-NamestringOptional
The name of the project that is making the request.

Request

Information about the fine-tuned model. Must contain name and settings.

namestringRequired

FinetunedModel name (e.g. foobar).

settingsobjectRequired
FinetunedModel settings such as dataset, hyperparameters...
statusenumOptionalDefaults to STATUS_UNSPECIFIED

Current stage in the life-cycle of the fine-tuned model.

Response

A successful response.
finetuned_modelobject

Information about the fine-tuned model.

Errors

400
Bad Request Error
401
Unauthorized Error
403
Forbidden Error
404
Not Found Error
500
Internal Server Error
503
Service Unavailable Error