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Llama_Stack_Building_AI_Applications.ipynb -> getting_started.ipynb (#854)

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Llama_Stack_Building_AI_Applications.ipynb -> getting_started.ipynb
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Dinesh Yeduguru 2025-01-23 12:04:06 -08:00 • committed by GitHub
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[![PyPI - Downloads](https://img.shields.io/pypi/dm/llama-stack)](https://pypi.org/project/llama-stack/)
[![Discord](https://img.shields.io/discord/1257833999603335178)](https://discord.gg/llama-stack)
[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Colab Notebook**](./docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb)
[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Colab Notebook**](./docs/getting_started.ipynb)
Llama Stack defines and standardizes the core building blocks that simplify AI application development. It codified best practices across the Llama ecosystem. More specifically, it provides
@ -97,7 +97,7 @@ Please checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest
* Guide using `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
* [Getting Started](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html)
* Quick guide to start a Llama Stack server.
* [Jupyter notebook](./docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
* [Jupyter notebook](./docs/getting_started.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
* The complete Llama Stack lesson [Colab notebook](https://colab.research.google.com/drive/1dtVmxotBsI4cGZQNsJRYPrLiDeT0Wnwt) of the new [Llama 3.2 course on Deeplearning.ai](https://learn.deeplearning.ai/courses/introducing-multimodal-llama-3-2/lesson/8/llama-stack).
* A [Zero-to-Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.
* [Contributing](CONTRIBUTING.md)