Principle:Cohere ai Cohere python Dataset Upload
| Field | Value |
|---|---|
| Type | Principle |
| Source | Cohere Python SDK |
| Domain | Data Ingestion Fine-tuning Dataset Management |
| Last Updated | 2026-02-15 |
| Implemented By | Implementation:Cohere_ai_Cohere_python_DatasetsClient_Create |
Overview
A data ingestion pattern for uploading training and evaluation datasets to Cohere's managed storage.
Description
Dataset Upload is the process of submitting structured data files to Cohere for use in fine-tuning or batch embedding jobs. The datasets API supports multiple formats (JSONL for chat fine-tuning, CSV for classification) and performs server-side validation of data structure. After upload, the SDK polls for validation completion using the wait utility before the dataset can be used in downstream jobs.
Usage
Upload datasets before creating fine-tuning or embed jobs. Use the appropriate DatasetType (e.g., "chat-finetune-input") and format (JSONL with chat turns). Monitor validation with wait().
Theoretical Basis
The upload-validate-reference pattern separates data ingestion from computation. Server-side validation catches formatting errors early. The polling pattern (wait utility) implements eventual consistency -- the dataset transitions through states until validated.