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.
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Guides and conceptsAPI ReferenceRelease NotesLLMUCookbooks
Guides and conceptsAPI ReferenceRelease NotesLLMUCookbooks
  • Get Started
    • Introduction
    • Installation
    • Creating a client
    • Playground
    • FAQs
  • Models
    • An Overview of Cohere's Models
    • Aya
    • Embed
    • Rerank
  • Text Generation
    • Introduction to Text Generation at Cohere
    • Using the Chat API
    • Reasoning
    • Image Inputs
    • Streaming Responses
    • Predictable Outputs
    • Advanced Generation Parameters
    • Tool Use
    • Tokens and Tokenizers
    • Summarizing Text
    • Safety Modes
  • Embeddings (Vectors, Search, Retrieval)
    • Introduction to Embeddings at Cohere
    • Semantic Search with Embeddings
    • Multimodal Embeddings
    • Batch Embedding Jobs
  • Going to Production
    • API Keys and Rate Limits
    • Going Live
    • Deprecations
    • How Does Cohere's Pricing Work?
  • Integrations
    • Integrating Embedding Models with Other Tools
    • Cohere and LangChain
    • LlamaIndex and Cohere
  • Deployment Options
    • Overview
    • SDK Compatibility
  • Tutorials
    • Cookbooks
    • LLM University
    • Build Things with Cohere!
    • Agentic RAG
    • Cohere on Azure
  • Responsible Use
    • Security
    • Usage Policy
    • Command A Technical Report
    • Command R and Command R+ Model Card
  • Cohere Labs
    • Cohere Labs Acceptable Use Policy
  • More Resources
    • Cohere Toolkit
    • Datasets
    • Improve Cohere Docs
    • FAQs / Troubleshooting
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On this page
  • How Long Does it Take to Train a Model?
  • Using Your Trained Model
  • Troubleshooting A Failed Training Run
  • FAQs
  • How do I Know if my Fine-tuned Model is Actually Better than the Base Model?
  • How Many Fine-tuning jobs can I have?
  • Will my Fine-tuned Models be Deleted?

FAQs for Troubleshooting A Fine-Tuned Model

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Cohere’s fine-tuning feature was deprecated on September 15, 2025

How Long Does it Take to Train a Model?

Trainings are completed sequentially, and when you launch a training session, it is added to the end of a queue. Depending on the length of our training queue, training may take between an hour and a day to complete.

Using Your Trained Model

To use your trained model in our API or SDKs, you must call it by its model UUID and not by its name. To get the model UUID, select the model in the playground and click Export Code. Select the language you are using and copy the code to call the model.

This is a screenshot of how to locate the model path to call your custom model.

Troubleshooting A Failed Training Run

Our engineers review every individual failed training run and will attempt to rectify it, without any action on your part. We reach out to individuals with failed custom models we cannot resolve manually.

FAQs

How do I Know if my Fine-tuned Model is Actually Better than the Base Model?

We recommend generating samples from both the base model and the fine-tuned model on a test set. Then, compare these examples directly through human evaluations.

How Many Fine-tuning jobs can I have?

Standard organizations are allowed 10 jobs per day (15 jobs in total), while enterprises are allowed 25 jobs per day (with no limit on total).

Will my Fine-tuned Models be Deleted?

No, we do not delete any fine-tuned models.

Please reach out to support@cohere.com or post in our Discord if you have unanswered questions about fine-tuning.