Add a meta-reference-quantized-gpu distribution

distributions/meta-reference-quantized-gpu/README.md

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+# Meta Reference Quantized Distribution
+
+The `llamastack/distribution-meta-reference-quantized-gpu` distribution consists of the following provider configurations.
+
+
+| **API**         	| **Inference**            	| **Agents**     	| **Memory**                                       	| **Safety**     	| **Telemetry**  	|
+|-----------------	|------------------------  	|----------------	|--------------------------------------------------	|----------------	|----------------	|
+| **Provider(s)** 	| meta-reference-quantized  | meta-reference 	| meta-reference, remote::pgvector, remote::chroma 	| meta-reference 	| meta-reference 	|
+
+The only difference vs. the `meta-reference-gpu` distribution is that it has support for more efficient inference -- with fp8, int4 quantization, etc.
+
+### Start the Distribution (Single Node GPU)
+
+> [!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.
+
+
+To download and start running a pre-built docker container, 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-quantized-gpu \
+  --yaml_config /root/my-run.yaml
+```
+
+### Alternative (Build and start distribution locally via conda)
+
+- You may checkout the [Getting Started](../../docs/getting_started.md) for more details on building locally via conda and starting up the distribution.

distributions/meta-reference-quantized-gpu/build.yaml

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+name: meta-reference-quantized-gpu
+distribution_spec:
+  docker_image: pytorch/pytorch:2.5.0-cuda12.4-cudnn9-runtime
+  description: Use code from `llama_stack` itself to serve all llama stack APIs
+  providers:
+    inference: meta-reference-quantized
+    memory:
+    - meta-reference
+    - remote::chromadb
+    - remote::pgvector
+    safety: meta-reference
+    agents: meta-reference
+    telemetry: meta-reference
+image_type: docker

distributions/meta-reference-quantized-gpu/run.yaml

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+version: '2'
+built_at: '2024-10-08T17:40:45.325529'
+image_name: local
+docker_image: null
+conda_env: local
+apis:
+- shields
+- agents
+- models
+- memory
+- memory_banks
+- inference
+- safety
+providers:
+  inference:
+  - provider_id: meta0
+    provider_type: meta-reference-quantized
+    config:
+      model: Llama3.2-3B-Instruct
+      quantization:
+        type: fp8
+      torch_seed: null
+      max_seq_len: 2048
+      max_batch_size: 1
+  safety:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config:
+      llama_guard_shield:
+        model: Llama-Guard-3-1B
+        excluded_categories: []
+        disable_input_check: false
+        disable_output_check: false
+      prompt_guard_shield:
+        model: Prompt-Guard-86M
+  memory:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config: {}
+  agents:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config:
+      persistence_store:
+        namespace: null
+        type: sqlite
+        db_path: ~/.llama/runtime/kvstore.db
+  telemetry:
+  - provider_id: meta0
+    provider_type: meta-reference
+    config: {}