Principle:Cohere ai Cohere python Finetuned Model Creation
| Field | Value |
|---|---|
| Type | Principle |
| Source | Cohere Python SDK |
| Domain | Fine-tuning Model Training Job Submission |
| Last Updated | 2026-02-15 |
| Implemented By | Implementation:Cohere_ai_Cohere_python_FinetuningClient_Create |
Overview
A process for submitting fine-tuning job configurations to create custom models on Cohere's platform.
Description
Finetuned Model Creation is the act of submitting a fully configured FinetunedModel to Cohere's training infrastructure. The API validates the configuration, allocates resources, and begins the training process. The returned response includes the model ID and initial status. Training is asynchronous -- the model transitions through status states (STATUS_FINETUNING -> STATUS_DEPLOYING_API -> STATUS_READY) as it progresses.
Usage
Call after configuring the FinetunedModel object. The response provides the model ID needed for monitoring and eventual inference.
Theoretical Basis
The asynchronous job submission pattern decouples configuration from execution. The status lifecycle (queued -> training -> deploying -> ready) reflects the multi-stage nature of model fine-tuning: validation, training, evaluation, and deployment.