From 4be99cc0d6897c95b384d528199507212ea31ca8 Mon Sep 17 00:00:00 2001 From: Trent Fowler Date: Wed, 18 Dec 2024 14:38:56 -0700 Subject: [PATCH] Adding an HF link. --- fern/pages/models/the-command-family-of-models/command-r7b.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/fern/pages/models/the-command-family-of-models/command-r7b.mdx b/fern/pages/models/the-command-family-of-models/command-r7b.mdx index a7ab875d..7565698d 100644 --- a/fern/pages/models/the-command-family-of-models/command-r7b.mdx +++ b/fern/pages/models/the-command-family-of-models/command-r7b.mdx @@ -12,7 +12,7 @@ updatedAt: '' --- -Command R7B is the smallest, fastest, and final model in our R family of enterprise-focused [large language models](https://docs.cohere.com/docs/introduction-to-large-language-models) (LLMs). With a context window of 128K, Command R7B offers state-of-the-art performance across a variety of real-world tasks, and is designed for use cases in which speed, cost, and compute are important. Command R7B is available today on the Cohere Platform as well as accessible on HuggingFace, or you can access it in the SDK with `command-r7b-12-2024`. For more information, check out our [dedicated blog post](https://cohere.com/blog/command-r7b). +Command R7B is the smallest, fastest, and final model in our R family of enterprise-focused [large language models](https://docs.cohere.com/docs/introduction-to-large-language-models) (LLMs). With a context window of 128K, Command R7B offers state-of-the-art performance across a variety of real-world tasks, and is designed for use cases in which speed, cost, and compute are important. Command R7B is available today on the Cohere Platform as well as accessible on [HuggingFace](https://huggingface.co/CohereForAI/c4ai-command-r7b-12-2024), or you can access it in the SDK with `command-r7b-12-2024`. For more information, check out our [dedicated blog post](https://cohere.com/blog/command-r7b). ## Model Details | Model Name | Description | Modality | Context Length | Maximum Output Tokens | Endpoints |