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Add pre-built alternative and _next-steps.md
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content/learning-paths/mobile-graphics-and-gaming/voice-sentiment-analysis-with-llm/2_set-up-your-environment.md

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Next, clone the [llama.cpp GitHub repository](https://github.com/ggml-org/llama.cpp), build the local inference server, and start it. This server exposes an OpenAI-compatible API that the Python application will call later in the Learning Path.
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{{% notice Pre-built llama.cpp %}}
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If you prefer not to build from source, you can use pre-built binaries from [llama.cpp releases](https://github.com/ggml-org/llama.cpp/releases). Download the package for your platform, extract it, and use the `llama-server` executable from that package in the run commands later in this section.
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{{% /notice %}}
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{{< tabpane code=true >}}
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{{< tab header="Ubuntu/macOS" language="bash">}}
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git clone https://github.com/ggml-org/llama.cpp
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---
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# ================================================================================
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# FIXED, DO NOT MODIFY THIS FILE
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# ================================================================================
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weight: 21 # Set to always be larger than the content in this path to be at the end of the navigation.
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title: "Next Steps" # Always the same, html page title.
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layout: "learningpathall" # All files under learning paths have this same wrapper for Hugo processing.
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---

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