Card: shorter vLLM Semantic Router command

The "Run with vLLM Semantic Router" section now uses `vllm-sr serve -e vllm-sr/d3-lite`: the platform is detected automatically, and one line lists the `--platform` values (auto, cpu, cuda, rocm; default auto). The parity sentence keeps its measurement context (AMD Instinct MI325X). MODEL_MANIFEST.json records the new README.md (SHA-256 and size) in the same commit. Weights, runtime files and the v3.1.0 tag are unchanged.

MODEL_MANIFEST.json

@@ -582,7 +582,7 @@
  "files_sha256": {
   "LICENSE": "c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4",
   "NOTICE": "e7fecd68cfb3c894924d48c642230cd2b96d3cf03ecc13907f5bcc55d52f3a9f",
-  "README.md": "640c6313f83abed0f876c745ee862c1a657861549e3691485b06728bb3897fb6",
+  "README.md": "c7eebb86c4ca4c098707da6a864c38e4df4797b33025153244d6146d41f2832a",
   "assets/banner.png": "5aef9308fc700d012c660d75a9f97976e4f1287afd15b46eb69fbd11bfc24949",
   "assets/example-receipt.png": "b9dbb8b103bacd45f1de824d844a3c07b81d57cb1a7466712ef060ad7dcb3926",
   "assets/example-video.mp4": "f4968ef89d07e97f20df4fd8047510a7a8e9df5c2d07c35e363a97927f164ab9",
@@ -613,7 +613,7 @@
  "files_bytes": {
   "LICENSE": 11357,
   "NOTICE": 106,
-  "README.md": 10379,
+  "README.md": 10473,
   "assets/banner.png": 2233930,
   "assets/example-receipt.png": 65918,
   "assets/example-video.mp4": 26300,

README.md

@@ -144,15 +144,17 @@ Images go before the text of the request, each read at up to 1.6 megapixels; vid
 
 ## Run with vLLM Semantic Router
 
-[vLLM Semantic Router](https://github.com/vllm-project/semantic-router) serves Decision 3.0 natively in Engine mode, which runs one model behind the System One API on your own machine. Its answers match this package's own `d3_server.py` exactly, for text, images and videos. On an AMD Instinct MI325X:
+[vLLM Semantic Router](https://github.com/vllm-project/semantic-router) serves Decision 3.0 natively in Engine mode, which runs one model behind the System One API on your own machine. Its answers match this package's own `d3_server.py` exactly, for text, images and videos (measured on AMD Instinct MI325X).
 
 ```bash
 curl -fsSL https://vllm-sr.ai/install.sh | bash -s -- --channel dev --no-launch
 export PATH="$HOME/.local/bin:$PATH"
-vllm-sr serve vllm-sr/d3-lite --engine --platform rocm
+vllm-sr serve -e vllm-sr/d3-lite
 ```
 
-Engine mode and Decision 3.0 are in the development channel (`--channel dev`) until a stable vLLM Semantic Router release includes them. The first start pulls the `vllm-sr-rocm` image and downloads the model. Then ask questions about a request:
+The platform is detected automatically; choose one with `--platform auto|cpu|cuda|rocm` (default `auto`).
+
+Engine mode and Decision 3.0 are in the development channel (`--channel dev`) until a stable vLLM Semantic Router release includes them. The first start pulls the image for your machine and downloads the model. Then ask questions about a request:
 
 ```bash
 curl -s localhost:8899/v1/systemone -H 'content-type: application/json' -d '{