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Enterprise fine-tuning suite

Optimize generative AI for performance by tailoring models to specific use cases and industries

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Why fine-tuning?

Leading Performance

Fine-tuning offers leading performance on enterprise use cases while costing less than the largest models on the market.

Greater Accuracy

By tailoring the model to specific use cases and industries, it can better understand and generate contextually relevant responses.

Improve Efficiency

Fine-tuning streamlines performance by reducing token usage and condensing the effectiveness of a larger model into a smaller, more efficient one.

Fine-tuning on Cohere Models

When should I fine-tune my model?

Fine-tuning is recommended when a pre-trained model doesn't perform your task well or when you want to teach it something new.


Create more relevant conversational experiences. Available on Command R.

Platform Availability

"The integration of Cohere’s technology marked a significant leap in performance… Cohere's fine-tuned models were easy to test, going live in less than an hour."

Nick Gibb
Machine Learning Engineer
01 / 02

Fine-tuning resources

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Cohere Docs

Learn how to fine-tune models for greater accuracy

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Customer Story

Discover how Bluedot doubles their classification accuracy

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Ready to get started?

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