update distributions compose/readme (#338)

* readme updates

* quantied compose

* dell tgi

* config update

distributions/dell-tgi/compose.yaml

@@ -0,0 +1,50 @@
+services:
+  text-generation-inference:
+    image: registry.dell.huggingface.co/enterprise-dell-inference-meta-llama-meta-llama-3.1-8b-instruct
+    network_mode: "host"
+    volumes:
+      - $HOME/.cache/huggingface:/data
+    ports:
+      - "5009:5009"
+    devices:
+      - nvidia.com/gpu=all
+    environment:
+      - CUDA_VISIBLE_DEVICES=0,1,2,3,4
+      - NUM_SHARD=4
+      - MAX_BATCH_PREFILL_TOKENS=32768
+      - MAX_INPUT_TOKENS=8000
+      - MAX_TOTAL_TOKENS=8192
+    command: []
+    deploy:
+      resources:
+        reservations:
+          devices:
+          - driver: nvidia
+            # that's the closest analogue to --gpus; provide
+            # an integer amount of devices or 'all'
+            count: all
+            # Devices are reserved using a list of capabilities, making
+            # capabilities the only required field. A device MUST
+            # satisfy all the requested capabilities for a successful
+            # reservation.
+            capabilities: [gpu]
+    runtime: nvidia
+  llamastack:
+    depends_on:
+      text-generation-inference:
+        condition: service_healthy
+    image: llamastack/distribution-tgi
+    network_mode: "host"
+    volumes:
+      - ~/.llama:/root/.llama
+      # Link to TGI run.yaml file
+      - ./run.yaml:/root/my-run.yaml
+    ports:
+      - "5000:5000"
+    # Hack: wait for TGI server to start before starting docker
+    entrypoint: bash -c "sleep 60; python -m llama_stack.distribution.server.server --yaml_config /root/my-run.yaml"
+    restart_policy:
+      condition: on-failure
+      delay: 3s
+      max_attempts: 5
+      window: 60s