# Open R1: How to use OlympicCoder locally for coding

DevFeed: [Open R1: How to use OlympicCoder locally for coding](<https://devfeed.tech/articles/open-r1-how-to-use-olympiccoder-locally-for-coding-7407.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/olympic-coder-lmstudio>)

Author: ben burtenshaw; Vaibhav Srivastav; Lewis Tunstall; Edward Beeching; Yagil Burowski

Published: 2025-03-20T00:00:00Z

Content type: tutorial

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [coding](<https://devfeed.tech/topics/coding.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [AI Models](<https://devfeed.tech/topics/ai-models.md>), [Local AI](<https://devfeed.tech/topics/local-ai.md>), [Visual Studio Code](<https://devfeed.tech/topics/visual-studio-code.md>), [quantization](<https://devfeed.tech/topics/quantization.md>), [VS Code Extension](<https://devfeed.tech/topics/vscode-extension.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Command-line interface](<https://devfeed.tech/topics/cli.md>)

Tags: [ai-models](<https://devfeed.tech/tags/ai-models.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [coding](<https://devfeed.tech/tags/coding.md>), [command-line](<https://devfeed.tech/tags/command-line.md>), [extension](<https://devfeed.tech/tags/extension.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [inference](<https://devfeed.tech/tags/inference.md>), [llm](<https://devfeed.tech/tags/llm.md>), [local](<https://devfeed.tech/tags/local.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [quantization](<https://devfeed.tech/tags/quantization.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [research](<https://devfeed.tech/tags/research.md>), [vscode](<https://devfeed.tech/tags/vscode.md>)

## AI overview

This tutorial explains how to run the OlympicCoder 7B coding model locally with LM Studio and integrate it into Visual Studio Code through the Continue extension. It covers quantized models, local inference, model downloads from the Hugging Face Hub, LM Studio's API server, and connecting VS Code to the local model.

## Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.