Add pipeline tag, library name, correct base model and add sample usage

README.md

@@ -1,14 +1,16 @@
 ---
-license: apache-2.0
 base_model:
-- Qwen/Qwen3-4B
+- Qwen/Qwen3-14B
 language:
-  - en
+- en
+license: apache-2.0
 tags:
-  - agent
-  - tool-use
-  - reinforcement-learning
-  - mcp
+- agent
+- tool-use
+- reinforcement-learning
+- mcp
+pipeline_tag: text-generation
+library_name: transformers
 ---
 
 <h1 align="center">Arctic-AWM-14B</h1>
@@ -29,11 +31,9 @@ tags:
   <sup>1</sup>UNC-Chapel Hill &nbsp; <sup>2</sup>Snowflake AI Research &nbsp;
 </p>
 
-
-
 # Overview
 
-**Arctic-AWM-14B** is a multi-turn tool-use agent model trained with agentic reinforcement learning on [Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B), using the fully synthetic environments from [AgentWorldModel-1K](https://huggingface.co/datasets/Snowflake/AgentWorldModel-1K).
+**Arctic-AWM-14B** is a multi-turn tool-use agent model trained with agentic reinforcement learning on [Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B), using the fully synthetic environments from [AgentWorldModel-1K](https://huggingface.co/datasets/Snowflake/AgentWorldModel-1K). It was introduced in the paper [Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement Learning](https://huggingface.co/papers/2602.10090).
 
 The model is trained to interact with tool-use environments exposed via a unified MCP (Model Context Protocol) interface, enabling strong multi-turn agentic capabilities.
 
@@ -52,6 +52,25 @@ Related resources are also available, please check:
 | 🤖 Arctic-AWM-8B | [🤗 Snowflake/Arctic-AWM-8B](https://huggingface.co/Snowflake/Arctic-AWM-8B) |
 | 🤖 Arctic-AWM-14B | [🤗 Snowflake/Arctic-AWM-14B](https://huggingface.co/Snowflake/Arctic-AWM-14B) |
 
+# Sample Usage
+
+You can use [vLLM](https://github.com/vllm-project/vllm) to serve the model and interact with it using the `awm` CLI provided in the [official repository](https://github.com/Snowflake-Labs/agent-world-model).
+
+```bash
+# serve the model
+vllm serve Snowflake/Arctic-AWM-14B --host 127.0.0.1 --port 8000
+
+# start the environment (example scenario)
+awm env start --scenario e_commerce_33 --envs_load_path outputs/gen_envs.jsonl --port 8001
+
+# run the agent
+awm agent \
+    --task "show me the top 10 most expensive products" \
+    --mcp_url http://localhost:8001/mcp \
+    --vllm_url http://localhost:8000/v1 \
+    --model Snowflake/Arctic-AWM-14B
+```
+
 # Citation
 
 If you find this resource useful, please kindly cite:
@@ -66,4 +85,4 @@ If you find this resource useful, please kindly cite:
       primaryClass={cs.AI},
       url={https://arxiv.org/abs/2602.10090}, 
 }
-```
+```