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7ee0ee7843
This change removes the `llama model` and `llama download` subcommands from the CLI, replacing them with recommendations to use the Hugging Face CLI instead. Rationale for this change: - The model management functionality was largely duplicating what Hugging Face CLI already provides, leading to unnecessary maintenance overhead (except the download source from Meta?) - Maintaining our own implementation required fixing bugs and keeping up with changes in model repositories and download mechanisms - The Hugging Face CLI is more mature, widely adopted, and better maintained - This allows us to focus on the core Llama Stack functionality rather than reimplementing model management tools Changes made: - Removed all model-related CLI commands and their implementations - Updated documentation to recommend using `huggingface-cli` for model downloads - Removed Meta-specific download logic and statements - Simplified the CLI to focus solely on stack management operations Users should now use: - `huggingface-cli download` for downloading models - `huggingface-cli scan-cache` for listing downloaded models This is a breaking change as it removes previously available CLI commands. Signed-off-by: Sébastien Han <seb@redhat.com> |
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| openapi_generator | ||
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| zero_to_hero_guide | ||
| docusaurus.config.ts | ||
| dog.jpg | ||
| getting_started.ipynb | ||
| getting_started_llama4.ipynb | ||
| getting_started_llama_api.ipynb | ||
| license_header.txt | ||
| original_rfc.md | ||
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| package.json | ||
| quick_start.ipynb | ||
| README.md | ||
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Llama Stack Documentation
Here's a collection of comprehensive guides, examples, and resources for building AI applications with Llama Stack. For the complete documentation, visit our Github page.
Render locally
From the llama-stack docs/ directory, run the following commands to render the docs locally:
npm install
npm run gen-api-docs all
npm run build
npm run serve
You can open up the docs in your browser at http://localhost:3000
Content
Try out Llama Stack's capabilities through our detailed Jupyter notebooks:
- Building AI Applications Notebook - A comprehensive guide to building production-ready AI applications using Llama Stack
- Benchmark Evaluations Notebook - Detailed performance evaluations and benchmarking results
- Zero-to-Hero Guide - Step-by-step guide for getting started with Llama Stack