forked from phoenix-oss/llama-stack-mirror
87 lines
2.7 KiB
Markdown
87 lines
2.7 KiB
Markdown
# Meta Reference Quantized Distribution
|
|
|
|
```{toctree}
|
|
:maxdepth: 2
|
|
:hidden:
|
|
|
|
self
|
|
```
|
|
|
|
The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations:
|
|
|
|
{{ providers_table }}
|
|
|
|
The only difference vs. the `meta-reference-gpu` distribution is that it has support for more efficient inference -- with fp8, int4 quantization, etc.
|
|
|
|
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.
|
|
|
|
{% if run_config_env_vars %}
|
|
### Environment Variables
|
|
|
|
The following environment variables can be configured:
|
|
|
|
{% for var, (default_value, description) in run_config_env_vars.items() %}
|
|
- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
|
|
{% endfor %}
|
|
{% endif %}
|
|
|
|
|
|
## Prerequisite: Downloading Models
|
|
|
|
Please make sure you have llama model checkpoints downloaded in `~/.llama` before proceeding. See [installation guide](https://llama-stack.readthedocs.io/en/latest/cli_reference/download_models.html) here to download the models. Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints.
|
|
|
|
```
|
|
$ ls ~/.llama/checkpoints
|
|
Llama3.1-8B Llama3.2-11B-Vision-Instruct Llama3.2-1B-Instruct Llama3.2-90B-Vision-Instruct Llama-Guard-3-8B
|
|
Llama3.1-8B-Instruct Llama3.2-1B Llama3.2-3B-Instruct Llama-Guard-3-1B Prompt-Guard-86M
|
|
```
|
|
|
|
## Running the Distribution
|
|
|
|
You can do this via Conda (build code) or Docker which has a pre-built image.
|
|
|
|
### Via Docker
|
|
|
|
This method allows you to get started quickly without having to build the distribution code.
|
|
|
|
```bash
|
|
LLAMA_STACK_PORT=5001
|
|
docker run \
|
|
-it \
|
|
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
|
|
llamastack/distribution-{{ name }} \
|
|
--port $LLAMA_STACK_PORT \
|
|
--env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
|
|
```
|
|
|
|
If you are using Llama Stack Safety / Shield APIs, use:
|
|
|
|
```bash
|
|
docker run \
|
|
-it \
|
|
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
|
|
llamastack/distribution-{{ name }} \
|
|
--port $LLAMA_STACK_PORT \
|
|
--env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
|
|
--env SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
|
|
```
|
|
|
|
### Via Conda
|
|
|
|
Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
|
|
|
|
```bash
|
|
llama stack build --template {{ name }} --image-type conda
|
|
llama stack run distributions/{{ name }}/run.yaml \
|
|
--port $LLAMA_STACK_PORT \
|
|
--env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
|
|
```
|
|
|
|
If you are using Llama Stack Safety / Shield APIs, use:
|
|
|
|
```bash
|
|
llama stack run distributions/{{ name }}/run-with-safety.yaml \
|
|
--port $LLAMA_STACK_PORT \
|
|
--env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
|
|
--env SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
|
|
```
|