doc: seo

jxnl · Feb 21, 2024 · 11c115c · 11c115c
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@@ -8,7 +8,7 @@ _Structured outputs powered by llms. Designed for simplicity, transparency, and
 [![Discord](https://img.shields.io/discord/1192334452110659664?label=discord)](https://discord.gg/CV8sPM5k5Y)
 [![Downloads](https://img.shields.io/pypi/dm/instructor.svg)](https://pypi.python.org/pypi/instructor)
 
-Instructor makes it easy to reliably get structured data like JSON from Large Language Models (LLMs) like GPT-3.5, GPT-4, GPT-4-Vision, including open source models like Mistral from [Together](./hub/together.md), [Anyscale](./hub/anyscale.md), [Ollama](./hub/ollama.md), and [llama-cpp-python](./hub/llama-cpp-python.md).
+Instructor makes it easy to reliably get structured data like JSON from Large Language Models (LLMs) like GPT-3.5, GPT-4, GPT-4-Vision, including open source models like Mistral/Mixtral from [Together](./hub/together.md), [Anyscale](./hub/anyscale.md), [Ollama](./hub/ollama.md), and [llama-cpp-python](./hub/llama-cpp-python.md).
 
 By leveraging various modes like Function Calling, Tool Calling and even constrained sampling modes like JSON mode, JSON Schema; Instructor stands out for its simplicity, transparency, and user-centric design. We leverage Pydantic to do the heavy lifting, and we've built a simple, easy-to-use API on top of it by helping you manage [validation context](./concepts/reask_validation.md), retries with [Tenacity](./concepts/retrying.md), and streaming [Lists](./concepts/lists.md) and [Partial](./concepts/partial.md) responses.