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README.md

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+# 📊 Nifty50GPT-Final — India's First Financial SQL LLM (Offline, Open-Source)
+
+**Nifty50GPT-Final** is a lightweight, offline-ready transformer model trained on structured Indian stock market data.  
+It was created by [Shubham Sood](https://www.linkedin.com/in/shubhamsood1) at **Student One Private Limited** 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
+- A bundled DuckDB database (`student_data.duckdb`) for instant access to 10+ years of data across 50+ NIFTY stocks, Indian indices, and global indices
+- Support for both CPU and GPU inference with zero dependencies on internet or live data
+
+---
+
+## 📦 What's Included
+
+| File                      | Description                                     |
+|---------------------------|-------------------------------------------------|
+| `pytorch_model.bin`       | Final trained LLM weights (TinyLLaMA-1.1B base) |
+| `tokenizer.json`          | Tokenizer configuration                         |
+| `config.json`             | Model configuration                             |
+| `special_tokens_map.json` | Special token mapping                           |
+| `student_data.duckdb`     | Historical Indian financial data                |
+| `README.md`               | You're reading it                               |
+
+---
+
+## ⚙️ How to Run (Inference on CPU or GPU)
+
+### 🖥️ Local Inference (CPU)
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model = AutoModelForCausalLM.from_pretrained("StudentOne/Nifty50GPT-Final")
+tokenizer = AutoTokenizer.from_pretrained("StudentOne/Nifty50GPT-Final")
+tokenizer.pad_token = tokenizer.eos_token
+
+prompt = "### Instruction: What was the net_profit of INFY on 2021-03-31?\n### Output:"
+inputs = tokenizer(prompt, return_tensors="pt")
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=100,
+    do_sample=False,
+    pad_token_id=tokenizer.pad_token_id,
+    eos_token_id=tokenizer.eos_token_id
+)
+
+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:
+Download DuckDB
+
+Launch DuckDB in terminal or PowerShell:
+
+Paste the SQL query generated by the model, for example:
+
+SELECT value FROM fundamentals
+WHERE stock_symbol = 'INFY'
+  AND metric = 'net_profit'
+  AND date = DATE '2021-03-31';
+
+
+⚡ 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?
+
+1. Fundamental Metric Lookups
+What was the net_profit of TCS on 2022-03-31?
+Give me the EPS of INFY on 2023-03-31
+
+2. All Fundamentals for a Company
+
+Give me all fundamental metrics for RELIANCE on 2021-03-31
+
+3. Year-over-Year Growth
+
+What was the YoY growth of net_profit for HDFCBANK?
+
+4. CAGR
+
+What was the 5-year CAGR of EPS for INFY from 2017 to 2022?
+
+5. OHLCV for Stocks or Indices
+
+Give me OHLCV for ASIANPAINT on 2023-01-20
+What was the close price of NIFTY50 on 2022-12-12?
+
+6. Rolling Metrics
+
+What was the 30-day moving average of close price for INFY on 2023-03-15?
+
+7. NIFTY-Wide Aggregates
+
+What was the average ROE across all NIFTY50 companies in 2022?
+
+
+# Supported Stock Symbols
+# Use stock symbols, not full company names. Examples:
+
+INFY, TCS, RELIANCE, HDFCBANK, ITC, ASIANPAINT, WIPRO,
+KOTAKBANK, ADANIENT, SBIN, LT, TECHM, COALINDIA, NESTLEIND
+
+
+indian indices-
+NIFTY50, SENSEX, NSEBANK, CNXIT, CNXPHARMA,
+CNXMEDIA, CNXENERGY, CNXAUTO, CNXMETAL, CNXREALTY
+
+global indices-
+S&P 500, Nasdaq 100, Dow Jones, FTSE 100,
+DAX, Nikkei 225, Hang Seng, Shanghai Composite
+
+
+📅 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
+Use exact stock symbols (INFY, not Infosys)
+
+Use supported metric names and date formats
+
+Follow the formats in this README for best results
+
+
+---
+
+## ⚠️ Legal Disclaimer
+
+This model and its associated database are provided **strictly for research, experimentation, and educational purposes** only.
+
+- **Nifty50GPT-Final does not provide financial advice.**
+- It does not guarantee accuracy, completeness, or relevance of any output.
+- It should not be used to make or inform investment decisions.
+- 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
+
+By using this model or dataset:
+- You acknowledge that **all responsibility lies with the user**.
+- Neither the author(s), contributors, nor affiliated organizations shall be held liable for any outcome, financial or otherwise, resulting from the use or misuse of this model or its outputs.
+
+This project is **not affiliated with the NSE, SEBI, or any regulatory or financial institution.**  
+This model is **not certified**, **audited**, or **approved** by any authority.
+
+> Use responsibly. Fork freely. Trust nothing. Verify everything.
+
+
+👨‍💼 Credits
+Created by Shubham Sood
+Maintained by Student One Private Limited
+🌐 www.studentone.tech
+🧠 Trained with ❤️ to make financial knowledge open, not gated.
+