[Doc] add embedding rerank doc (#7364)

docs/supported_models/rerank_models.md

@@ -0,0 +1,49 @@
+# Rerank Models
+
+SGLang offers comprehensive support for rerank models by incorporating optimized serving frameworks with a flexible programming interface. This setup enables efficient processing of cross-encoder reranking tasks, improving the accuracy and relevance of search result ordering. SGLang’s design ensures high throughput and low latency during reranker model deployment, making it ideal for semantic-based result refinement in large-scale retrieval systems.
+
+```{important}
+They are executed with `--is-embedding` and some may require `--trust-remote-code`
+```
+
+## Example Launch Command
+
+```shell
+python3 -m sglang.launch_server \
+  --model-path BAAI/bge-reranker-v2-m3 \
+  --host 0.0.0.0 \
+  --disable-radix-cache \
+  --chunked-prefill-size -1 \
+  --attention-backend triton \
+  --is-embedding \
+  --port 30000
+```
+
+## Example Client Request
+
+```python
+import requests
+
+url = "http://127.0.0.1:30000/v1/rerank"
+
+payload = {
+    "model": "BAAI/bge-reranker-v2-m3",
+    "query": "what is panda?",
+    "documents": [
+        "hi",
+        "The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China."
+    ]
+}
+
+response = requests.post(url, json=payload)
+response_json = response.json()
+
+for item in response_json:
+    print(f"Score: {item['score']:.2f} - Document: '{item['document']}'")
+```
+
+## Supported rerank models
+
+| Model Family (Rerank)                          | Example HuggingFace Identifier       | Chat Template | Description                                                                                                                      |
+|------------------------------------------------|--------------------------------------|---------------|----------------------------------------------------------------------------------------------------------------------------------|
+| **BGE-Reranker (BgeRerankModel)**              | `BAAI/bge-reranker-v2-m3`            | N/A           | Currently only support `attention-backend`   `triton` and `torch_native`.  high-performance cross-encoder reranker model from BAAI. Suitable for reranking search results based on semantic relevance.   |