Enterprise fine-tuning suite

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

Why fine-tuning?

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.

Generate

Enhance products with domain-specific text. Available on Command Light.

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 GibbMachine Learning Engineer
BlueDot
01 / 02

Fine-tuning resources

Cohere Docs

Learn how to fine-tune models for greater accuracy

CONTINUE IN DOCS

Customer Story

Discover how Bluedot doubles their classification accuracy

Learn more

Ready to get started?

Create an account and build with Cohere