Update README.md

README.md

@@ -1,7 +1,7 @@
 # 📊 Nifty50GPT-Final — India's First Financial SQL LLM (Offline, Open-Source)
 
 **Nifty50GPT-Final** is a lightweight, offline-ready transformer model fine tuned on structured Indian stock market data.  
-It was created by [Shubham Sood]() at **Student One** to make financial analysis transparent, free, and locally usable — without APIs or cloud dependencies.
+It was created by [Shubham Sood] at **Student One** to make financial analysis transparent, free, and locally usable — without APIs or cloud dependencies.
 
 This release includes:
 - A fully fine-tuned language model that generates **SQL queries** on structured prompts
@@ -10,7 +10,7 @@ This release includes:
 
 ---
 
-## 📦 What's Included
+## What's Included
 
 | File                      | Description                                     |
 |---------------------------|-------------------------------------------------|
@@ -23,9 +23,9 @@ This release includes:
 
 ---
 
-## ⚙️ How to Run (Inference on CPU or GPU)
+##  How to Run (Inference on CPU or GPU)
 
-### 🖥️ Local Inference (CPU)
+###  Local Inference (CPU)
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
@@ -53,7 +53,7 @@ print(tokenizer.decode(outputs[0]))
 ###DuckDB Integration (student_data.duckdb)
 All responses from Nifty50GPT-Final are SQL-ready and designed to be run on student_data.duckdb.
 
-🪛 How to Use It:
+ How to Use It:
 Download DuckDB
 
 Launch DuckDB in terminal or PowerShell:
@@ -66,11 +66,11 @@ WHERE stock_symbol = 'INFY'
   AND date = DATE '2021-03-31';
 
 
-⚡ Works instantly. No server, no latency, no setup.
+ Works instantly. No server, no latency, no setup.
 You can extend the dataset while keeping the schema the same
 
 
-### 📌 What Can I Ask Nifty50-GPT?
+###  What Can I Ask Nifty50-GPT?
 
 1. Fundamental Metric Lookups
 What was the net_profit of TCS on 2022-03-31?
@@ -118,13 +118,13 @@ S&P 500, Nasdaq 100, Dow Jones, FTSE 100,
 DAX, Nikkei 225, Hang Seng, Shanghai Composite
 
 
-📅 Supported Date Format
+ Supported Date Format
 
 YYYY-03-31 - all yearly fundamentals have been shown to be reported on 31st of every march
 
 YYYY-MM-DD for the rest
 
-⚠️ Tips to Avoid Hallucination
+Tips to Avoid Hallucination
 Use exact stock symbols (INFY, not Infosys)
 
 Use supported metric names and date formats
@@ -134,7 +134,7 @@ Follow the formats in this README for best results
 
 ---
 
-## ⚠️ Legal Disclaimer
+## Legal Disclaimer
 
 This model and its associated database are provided **strictly for research, experimentation, and educational purposes** only.
 
@@ -144,7 +144,7 @@ This model and its associated database are provided **strictly for research, exp
 - Outputs may be outdated, incorrect, or misinterpreted if used outside the documented prompt structure.
 - The included `student_data.duckdb` file is a static, sample database and may not reflect the most current financial data.
 
-### 🔒 No Liability
+### No Liability
 
 By using this model or dataset:
 - You acknowledge that **all responsibility lies with the user**.
@@ -156,8 +156,8 @@ This model is **not certified**, **audited**, or**approved** by any authority.
 > Use responsibly. Fork freely. Trust nothing. Verify everything.
 
 
-👨‍💼 Credits
+Credits
 Created by Shubham Sood
-Maintained by Student One Private Limited
-🌐 www.studentone.tech🧠 Trained with ❤️ to make financial knowledge open, not gated.
+Maintained by Student One
+🌐 www.studentone.tech