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---------

Co-authored-by: dltn <6599399+dltn@users.noreply.github.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
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# Meta Reference Distribution
The `llamastack/distribution-meta-reference-gpu` distribution consists of the following provider configurations.
| **API** | **Inference** | **Agents** | **Memory** | **Safety** | **Telemetry** |
|----------------- |--------------- |---------------- |-------------------------------------------------- |---------------- |---------------- |
| **Provider(s)** | meta-reference | meta-reference | meta-reference, remote::pgvector, remote::chroma | meta-reference | meta-reference |
### Step 0. 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.
```
$ 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
```
### Step 1. Start the Distribution
#### (Option 1) Start with Docker
```
$ cd distributions/meta-reference-gpu && docker compose up
```
> [!NOTE]
> This assumes you have access to GPU to start a local server with access to your GPU.
> [!NOTE]
> `~/.llama` should be the path containing downloaded weights of Llama models.
This will download and start running a pre-built docker container. Alternatively, you may use the following commands:
```
docker run -it -p 5000:5000 -v ~/.llama:/root/.llama -v ./run.yaml:/root/my-run.yaml --gpus=all distribution-meta-reference-gpu --yaml_config /root/my-run.yaml
```
#### (Option 2) Start with Conda
1. Install the `llama` CLI. See [CLI Reference](https://llama-stack.readthedocs.io/en/latest/cli_reference/index.html)
2. Build the `meta-reference-gpu` distribution
```
$ llama stack build --template meta-reference-gpu --image-type conda
```
3. Start running distribution
```
$ cd distributions/meta-reference-gpu
$ llama stack run ./run.yaml
```
### (Optional) Serving a new model
You may change the `config.model` in `run.yaml` to update the model currently being served by the distribution. Make sure you have the model checkpoint downloaded in your `~/.llama`.
```
inference:
- provider_id: meta0
provider_type: meta-reference
config:
model: Llama3.2-11B-Vision-Instruct
quantization: null
torch_seed: null
max_seq_len: 4096
max_batch_size: 1
```
Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints.