Improve model card: Add pipeline tag, library name, and explicit links

This PR enhances the model card for FunReason-MT-4B by:

- Adding `pipeline_tag: text-generation` to improve discoverability on the Hugging Face Hub.
- Adding `library_name: transformers` as evidence from `config.json` (transformers_version) and the usage of `tokenizer.apply_chat_template` indicates compatibility with the Hugging Face Transformers library. This will enable the automated "how to use" widget.
- Updating the top badge section to include explicit links to the Hugging Face paper page ([https://huggingface.co/papers/2510.24645](https://huggingface.co/papers/2510.24645)), the GitHub repository ([https://github.com/inclusionAI/AWorld-RL](https://github.com/inclusionAI/AWorld-RL)), and the overarching project page ([https://github.com/inclusionAI/AWorld](https://github.com/inclusionAI/AWorld)).
- Updating the reference to "full usage" to point to the main GitHub repository rather than a specific pull request.

The existing descriptive content and usage example have been preserved without alteration, in line with the contribution guidelines.

Please review and merge these improvements.

README.md

@@ -1,24 +1,24 @@
 ---
-license: apache-2.0
 base_model:
 - Qwen/Qwen3-4B-Instruct-2507
-task_categories:
-- question-answering
-- text-generation
 language:
 - en
+license: apache-2.0
 tags:
 - agent
 - Agentic Learning
 - tool use
 - BFCL
+task_categories:
+- question-answering
+- text-generation
+pipeline_tag: text-generation
+library_name: transformers
 ---
 
-
 # FunReason-MT Technical Report: Overcoming the Complexity Barrier in Multi-Turn Function Calling
 
-[![arXiv](https://img.shields.io/badge/arXiv-2510.24645-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2510.24645) [![Model](https://img.shields.io/badge/Hugging%20Face-Model-yellow?logo=huggingface)](https://huggingface.co/Bingguang/FunReason-MT) [![Dataset](https://img.shields.io/badge/Hugging%20Face-Dataset-yellow?logo=huggingface)](https://huggingface.co/datasets/Bingguang/FunReason-MT)
-
+[![arXiv](https://img.shields.io/badge/arXiv-2510.24645-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2510.24645) [![Paper](https://img.shields.io/badge/Hugging%20Face-Paper-yellow?logo=huggingface)](https://huggingface.co/papers/2510.24645) [![Model](https://img.shields.io/badge/Hugging%20Face-Model-yellow?logo=huggingface)](https://huggingface.co/Bingguang/FunReason-MT) [![Dataset](https://img.shields.io/badge/Hugging%20Face-Dataset-yellow?logo=huggingface)](https://huggingface.co/datasets/Bingguang/FunReason-MT) [![GitHub](https://img.shields.io/badge/GitHub-Code-181717?logo=github)](https://github.com/inclusionAI/AWorld-RL) [![Project Page](https://img.shields.io/badge/Project-AWorld-green)](https://github.com/inclusionAI/AWorld)
 
 ## Model Overview
 
@@ -30,9 +30,7 @@ FunReason-MT-4B achieves state-of-the-art results on the **Berkeley Function-Cal
   - **Size:** 4 Billion parameters
   - **Key Capability:** Advanced Multi-Turn Function Calling and Agentic Tool-Use 
 
-The full usage of the model is in this [pull request](https://github.com/ShishirPatil/gorilla/pull/1229)
-
-
+The full usage of the model is in the [AWorld-RL GitHub repository](https://github.com/inclusionAI/AWorld-RL).
 
 
 ## 📊 Evaluation Results
@@ -195,8 +193,11 @@ class FunReasonMTHandler(OSSHandler):
         cleaned_response = model_response
         if "</think>" in model_response:
             parts = model_response.split("</think>")
-            reasoning_content = parts[0].rstrip("\n").split("<think>")[-1].lstrip("\n")
-            cleaned_response = parts[-1].lstrip("\n")
+            reasoning_content = parts[0].rstrip("
+").split("<think>")[-1].lstrip("
+")
+            cleaned_response = parts[-1].lstrip("
+")
         else:
             cleaned_response = "response outputs too long or no slash think in response."
         print("cleaned_response: ", cleaned_response)