Enterprise fine-tuning suite
Optimize generative AI for performance by tailoring models to specific use cases and industries
Enterprise fine-tuning suite
Enterprise fine-tuning suite
Optimize generative AI for performance by tailoring models to specific use cases and industries
Enterprise fine-tuning suite
Our Customers
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.
Command
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."
— Machine Learning Engineer
BlueDot
Fine-tuning resources
Cohere Docs
Learn how to fine-tune models for greater accuracy