Update README.md

README.md

@@ -79,13 +79,21 @@ II-Search-4B is designed for:
 - Educational and research applications requiring factual accuracy
 
 ## Usage
-
+To deploy and interact with the II-Search-4B model effectively, follow these options:
+1. Serve the model using vLLM or SGLang
+Use the following command to serve the model with vLLM (adjust parameters as needed for your hardware setup):
 ```bash
 vllm serve Intelligent-Internet/II-Search-4B --served-model-name II-Search-4B --tensor-parallel-size 8 --enable-reasoning --reasoning-parser deepseek_r1 --rope-scaling '{"rope_type":"yarn","factor":1.5,"original_max_position_embeddings":98304}' --max-model-len 131072
 ```
-- Or you can host the [II-4B-Search-MLX ](https://huggingface.co/Intelligent-Internet/II-Search-4B-MLX/) on your Mac then use LMStudio/ Olama Desktop to use it.
+This configuration enables distributed tensor parallelism across 8 GPUs, reasoning capabilities, custom RoPE scaling for extended context, and a maximum context length of 131,072 tokens.
+
+2. Integrate web_search and web_visit tools
+Equip the served model with web_search and web_visit tools to enable internet-aware functionality. Alternatively, use a middleware like MCP for tool integration—see this example repository: https://github.com/hoanganhpham1006/mcp-server-template.
 
-### Recommended Generation Parameters
+## Host on macOS with MLX for local use
+ As an alternative for Apple Silicon users, host the quantized [II-Search-4B-MLX](https://huggingface.co/Intelligent-Internet/II-Search-4B-MLX) version on your Mac. Then, interact with it via user-friendly interfaces like LM Studio or Ollama Desktop.
+
+## Recommended Generation Parameters
 
 ```python
 generate_cfg = {
@@ -95,7 +103,6 @@ generate_cfg = {
     'repetition_penalty': 1.1,
     'max_tokens': 2048
 }
-
 ```
 
 - For a query that you need to find a short and accurate answer. Add the following phrase: "\n\nPlease reason step-by-step and put the final answer within \\boxed{}."