# Learning Paths

AFM Learning Paths provide step-by-step instructions on how to deploy AFM models on various platforms. These learning paths provide insight on the model, serving libraries, and the hardware they're run on. 

Select any of the paths below to start your journey of running AI efficiently, securely, and cost effectively:

| Title                                                                | Who it's for                                                                                                                                                    | Link                                                                                                                   |
| -------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- |
| Deploy Arcee AFM-4.5B on Arm-based Google Cloud Axion with Llama.cpp | This Learning Path is for developers and ML engineers who want to deploy Arcee's AFM-4.5B small language model on Google Cloud Axion instances using Llama.cpp. | [Go to learning path](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arcee-foundation-model-on-gcp/) |
| Deploy Arcee AFM-4.5B on Arm-based AWS Graviton4 with Llama.cpp      | This Learning Path is for developers and ML engineers who want to deploy Arcee's AFM-4.5B small language model on AWS Graviton4 instances using Llama.cpp.      | [Go to learning path](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arcee-foundation-model-on-aws/) |


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.arcee.ai/other/learning-paths.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.