An Overview of Cohere’s Models
Cohere has a variety of models that cover many different use cases. If you need more customization, you can train a model to tune it to your specific use case.
Cohere models are currently available on the following platforms:
At the end of each major section below, you’ll find technical details about how to call a given model on a particular platform.
What can These Models Be Used For?
In this section, we’ll provide some high-level context on Cohere’s offerings, and what the strengths of each are.
- The Command family of models includes Command A, Command R7B, Command R+, Command R, and Command. Together, they are the text-generation LLMs powering tool-using agents, retrieval augmented generation (RAG), translation, copywriting, and similar use cases. They work through the Chat endpoint, which can be used with or without RAG.
- Rerank is the fastest way to inject the intelligence of a language model into an existing search system. It can be accessed via the Rerank endpoint.
- Embed improves the accuracy of search, classification, clustering, and RAG results. It also powers the Embed and Classify endpoints.
- The Aya family of models are aimed at expanding the number of languages covered by generative AI. Aya Expanse covers 23 languages, and Aya Vision is fully multimodal, allowing you to pass in images and text and get a single coherent response. Both are available on the Chat endpoint.
Command
Command is Cohere’s default generation model that takes a user instruction (or command) and generates text following the instruction. Our Command models also have conversational capabilities which means that they are well-suited for chat applications.
Using Command Models on Different Platforms
In this table, we provide some important context for using Cohere Command models on Amazon Bedrock, Amazon SageMaker, and more.
Embed
These models can be used to generate embeddings from text or classify it based on various parameters. Embeddings can be used for estimating semantic similarity between two sentences, choosing a sentence which is most likely to follow another sentence, or categorizing user feedback, while outputs from the Classify endpoint can be used for any classification or analysis task. The Representation model comes with a variety of helper functions, such as for detecting the language of an input.
Using Embed Models on Different Platforms
In this table, we provide some important context for using Cohere Embed models on Amazon Bedrock, Amazon SageMaker, and more.
Rerank
The Rerank model can improve created models by re-organizing their results based on certain parameters. This can be used to improve search algorithms.
Using Rerank Models on Different Platforms
In this table, we provide some important context for using Cohere Rerank models on Amazon Bedrock, SageMaker, and more.
Rerank accepts full strings rather than tokens, so the token limit works a little differently. Rerank will automatically chunk documents longer than 510 tokens, and there is therefore no explicit limit to how long a document can be when using rerank. See our best practice guide for more info about formatting documents for the Rerank endpoint.
Aya
Aya is a family of multilingual large language models designed to expand the number of languages covered by generative AI for purposes of research and to better-serve minority linguistic communities.
Its 8-billion and 32-billion parameter “Expanse” offerings are optimized to perform well in these 23 languages: Arabic, Chinese (simplified & traditional), Czech, Dutch, English, French, German, Greek, Hebrew, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese.
Its 8-billion and 32-billion parameter “Vision” models are state-of-the-art multimodal models excelling at a variety of critical benchmarks for language, text, and image capabilities.
Using Aya Models on Different Platforms
Aya isn’t available on other platforms, but it can be used with WhatsApp. Find more information here.