Update README.md

README.md

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----
-license: apache-2.0
-tags:
-  - reinforcement-learning
-  - q-learning
-  - taxi-agent
-  - gym
-  - python
-library_name: gym
----
-
-# Taxi-v3 Q-Learning Agent
-
-This repository contains a trained Q-learning agent for the Taxi-v3 environment from OpenAI Gym. The agent is stored as a `q_table.npy` file.
-
-
-
-
-
-
-# RL-Taxi Agent
-
-This project implements a **Q-learning agent** for the **OpenAI Gym Taxi-v3 environment**.  
-The agent is trained to pick up and drop off passengers efficiently while maximizing the total reward.
-
----
-
-## Features
-
-- **Environment:** OpenAI Gym `Taxi-v3`
-- **Algorithm:** Q-learning
-- **Visualization:**  
-  - Terminal ASCII render of the Taxi environment  
-  - Optional `pygame` GUI render
-- **Trained Model:** Q-table stored on [Hugging Face](https://huggingface.co/jatinror/taxi-q-table/resolve/main/q_table.npy)
-- **Python 3.10+** compatible
-- **Direct Hugging Face Integration:** Load Q-table without storing locally
-
----
-
-## Installation
-
-1. Clone the repository:
-
-```bash
-git clone <your-repo-url>
-cd RL-Taxi
+---
+license: apache-2.0
+tags:
+  - reinforcement-learning
+  - q-learning
+  - taxi-agent
+  - gym
+  - python
+library_name: gym
+---
+
+# 🚖 Taxi-v3 Q-Learning Agent
+
+This repository contains a trained **Q-learning agent** for the `Taxi-v3` environment.
+
+The agent learns to efficiently pick up and drop off passengers while maximizing reward using a tabular Q-learning approach.
+
+The trained model is packaged as `model.zip`, which contains the learned `q_table.npy`.
+
+---
+
+## 📌 Environment Details
+
+- **Environment:** `Taxi-v3`
+- **Algorithm:** Q-learning (Tabular RL)
+- **State Space:** 500 discrete states
+- **Action Space:** 6 discrete actions
+- **Training Episodes:** 20,000+
+- **Framework:** OpenAI Gym / Gymnasium compatible
+
+---
+
+## 📦 Model File
+
+The trained agent is stored as:
+