Our APIs no longer require a model to be specified. Each endpoint comes with great defaults. For more control, a model can still be specified by adding a model param in the request.

Updated small, medium, and large models are more stable and resilient against abnormal inputs due to a FP16 quantization fix. We also fixed a bug in generation presence & frequency penalty, which will result in more effective penalties.

Our new and improved xlarge has better generation quality and a 4x faster prediction speed. This model now supports a maximum token length of 2048 tokens and frequency and presence penalties.

We've retrained our small, medium, and large generation and representation models. Updated representation models now support contexts up to 4096 tokens (previously 1024 tokens). We recommend keeping text lengths below 512 tokens for optimal performance; for any text longer than 512 tokens, the text is spliced and the resulting embeddings of each component are then averaged and returned.

Finetuning is Generally Available

We’ve shipped updated small, medium, and large generation models. You’ll find significant improvements in performance that come from our newly assembled high quality dataset.

Classification is now available via our classification endpoint. This endpoint is currently powered by our generation models (small and medium) and supports few-shot classification. We will be deprecating support for Choose Best by May 18th. To learn more about classification at Cohere check out the docs here.

Our biggest and most performant generation model is now available. Extremely Large (Beta) outperforms our previous large model on a variety of downstream tasks including sentiment analysis, named entity recognition (NER) and common sense reasoning, as measured by our internal benchmarks. You can access Extremely Large (Beta) as xlarge-20220301. While in Beta, note that this model will have a maximum token length of 1024 tokens and maximum num_generations of 1.

Representation Models are now available in the sizes of medium-20220217 and large-20220217 as well as an updated version of small-20220217. Our previous small model will be available as small-20211115. In addition, the maximum tokens length per text has increased from 512 to 1024. We recommend keeping text lengths below 128 tokens for optimal performance; for any text longer than 128 tokens, the text is spliced and the resulting embeddings of each component are then averaged and returned.