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https://github.com/meta-llama/llama-stack.git
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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>
89 lines
2.3 KiB
Markdown
89 lines
2.3 KiB
Markdown
---
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orphan: true
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---
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# Meta Reference GPU Distribution
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```{toctree}
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:maxdepth: 2
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:hidden:
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self
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```
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The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations:
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{{ providers_table }}
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Note that you need access to nvidia GPUs to run this distribution. This distribution is not compatible with CPU-only machines or machines with AMD GPUs.
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{% if run_config_env_vars %}
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### Environment Variables
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The following environment variables can be configured:
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{% for var, (default_value, description) in run_config_env_vars.items() %}
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- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
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{% endfor %}
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{% endif %}
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## Prerequisite: Downloading Models
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Please check that you have llama model checkpoints downloaded in `~/.llama` before proceeding. See [installation guide](../../references/llama_cli_reference/download_models.md) here to download the models using the Hugging Face CLI.
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```
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## Running the Distribution
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You can do this via venv or Docker which has a pre-built image.
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### Via Docker
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This method allows you to get started quickly without having to build the distribution code.
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```bash
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LLAMA_STACK_PORT=8321
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docker run \
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-it \
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--pull always \
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--gpu all \
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-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
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-v ~/.llama:/root/.llama \
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-e INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
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llamastack/distribution-{{ name }} \
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--port $LLAMA_STACK_PORT
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```
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If you are using Llama Stack Safety / Shield APIs, use:
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```bash
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docker run \
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-it \
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--pull always \
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--gpu all \
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-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
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-v ~/.llama:/root/.llama \
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-e INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
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-e SAFETY_MODEL=meta-llama/Llama-Guard-3-1B \
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llamastack/distribution-{{ name }} \
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--port $LLAMA_STACK_PORT
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```
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### Via venv
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Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
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```bash
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llama stack build --distro {{ name }} --image-type venv
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INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
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llama stack run distributions/{{ name }}/run.yaml \
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--port 8321
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```
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If you are using Llama Stack Safety / Shield APIs, use:
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```bash
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INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
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SAFETY_MODEL=meta-llama/Llama-Guard-3-1B \
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llama stack run distributions/{{ name }}/run-with-safety.yaml \
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--port 8321
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```
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