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Command R+ is an instruction-following conversational model that performs language tasks at a higher quality, more reliably, and with a longer context than previous models. It is best suited for complex RAG workflows and multi-step tool use.
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Command R+ is Cohere's optimized for conversational interaction and long-context tasks, best suited for complex RAG workflows and multi-step tool use.
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Command R is a conversational model that excels in language tasks and supports multiple languages, making it ideal for coding use cases.
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A smaller, faster version of command . Almost as capable, but a lot faster.
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An instruction-following conversational model that performs language tasks with high quality, more reliably and with a longer context than our base generative models.
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A model that allows for text and images to be classified or turned into embeddings
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A model that allows for text to be classified or turned into embeddings. English only.
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A smaller, faster version of embed-english-v3.0 . Almost as capable, but a lot faster. English only.
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Provides multilingual classification and embedding support. See supported languages here.
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A smaller, faster version of embed-multilingual-v3.0 . Almost as capable, but a lot faster. Supports multiple languages.
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A multilingual model that allows for re-ranking English and non-english documents and semi-structured data (JSON). This is better suited for state-of-the-art quality and complex use-cases than its fast variant.
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A light version of rerank-v4.0-pro , this is a multilingual model that allows for re-ranking English and non-english documents and semi-structured data (JSON). This model is better suited for low latency and high throughput use-cases than its pro variant.
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A model for documents and semi-structured data (JSON). Performs well in English and non-English languages; supports the same languages as embed-multilingual-v3.0. This model has a context length of 4096 tokens
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A model that allows for re-ranking English Language documents and semi-structured data (JSON). This model has a context length of 4096 tokens.
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A model for documents and semi-structure data (JSON) that are not in English. Supports the same languages as embed-multilingual-v3.0 . This model has a context length of 4096 tokens.
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This page describes how the Cohere Transcribe model works and how to use it.
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Tiny Aya Global is a 3.35B instruction-tuned multilingual model with the best balance across languages and regions. Supports 70 languages.
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Tiny Aya Earth is a 3.35B region-specialized multilingual model, best for West Asian and African languages. Supports 70 languages.
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Tiny Aya Fire is a 3.35B region-specialized multilingual model, best for South Asian languages. Supports 70 languages.
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Tiny Aya Water is a 3.35B region-specialized multilingual model, best for European and Asia-Pacific languages. Supports 70 languages.
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