Update README.md

README.md

@@ -31,7 +31,7 @@ The primary objective of this model is to **serve the unique needs of Indian sto
 
 <p align="center">
   <img src="https://huggingface.co/bhaskartripathi/GPT_Neo_Market_Analysis/resolve/main/indicBull.JPG" alt="IndicFinGPT Logo" width="400" height="300">
-  <strong>भारत का पहला AI मॉडल: शीर्ष 100 कंपनियों पर केंद्रित</strong>
+  <strong>भारत बाजार की शीर्ष 100 कंपनियों का वित्तीय विश्लेषण करने वाला पहला Small Language Model</strong>
 </p>
 
 
@@ -43,21 +43,64 @@ The training data also incorporates **local influences** such as cultural factor
 
 ## Key Highlights
 
-IndicFinGPT
-India's first Large Language Model fine-tuned for financial market analysis, built on GPT-Neo 125M architecture.
-Key Highlights
-IndicFinGPT is the first LLM tailored for Indian financial markets, providing in-depth insights into:
+1. Trading Patterns: Specialized in recognizing BSE/NSE-specific patterns and cycles
+2. Market Sentiment: Built-in understanding of Indian market sentiment and cultural influences
+3. Macro-Economic Indicators: Adapted to domestic economic and financial metrics
+4. Indian Economic Influences: Awareness of timing, festival impacts, and market-specific volatility
+5. 10+ Technical Indicators
 
-Trading Patterns: Specialized in recognizing BSE/NSE-specific patterns and cycles
-Market Sentiment: Built-in understanding of Indian market sentiment and cultural influences
-Economic Indicators: Adapted to domestic economic and financial metrics
-Local Influences: Awareness of timing, festival impacts, and market-specific volatility
+## Implementation
+
+### Quick Start
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained("bhaskartripathi/GPT_Neo_Market_Analysis")
+tokenizer = AutoTokenizer.from_pretrained("bhaskartripathi/GPT_Neo_Market_Analysis")
+
+input_text = '''[INST] Given the following stock market data and technical analysis:
+Stock: EXAMPLE
+Date: 2024-01-01
+Technical Analysis:
+Current Price: ₹100
+Daily Range: ₹98 - ₹102
+Trading Volume: 1,000,000
+RSI: 55
+MACD: Bullish
+Based on this technical analysis, what is the likely price movement for tomorrow and why? [/INST]'''
+
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=50)
+result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+```
+
+## Training Details
 
+### Dataset and Fine-tuning
+- **Dataset**: Comprehensive dataset featuring 6 years of Indian market data.
+- **Method**: Fine-tuned using QLoRA (4-bit quantization) for optimal efficiency.
+- **Training Infrastructure**: Utilized an Nvidia T4 GPU, trained for ~6 hours with PEFT framework version 0.13.2.
 
+## Performance Metrics
+- **Pattern Recognition**: High accuracy in classical and advanced pattern detection in Indian markets.
+- **Sentiment Correlation**: Strong alignment with local market movements.
+- **Risk & Volatility Handling**: Reliable risk analysis in volatile market conditions.
+
+## Use Cases
+
+- **Automated Market Analysis**: Insight generation for Indian stock portfolios.
+- **Strategy Development**: Recommendations for traders in local markets.
+- **Risk Management**: Portfolio analysis and risk mitigation insights.
+- **Educational Utility**: Training tool for new traders learning about Indian markets.
+
+## Social Impact
+
+IndicFinGPT democratizes sophisticated AI-based financial analysis for the Indian stock market, providing affordable and accessible tools for both seasoned investors and new traders.
 
 ## Core Capabilities
 
 #### Automated Q&A based Technical Analysis for chartless Trading:
+Investors, Traders, Economists, Econometricians and Researchers can ask any types of questions related to the below areas:
 
 - **Head and Shoulders patterns**
   - What are the implications of a Head and Shoulders pattern forming for Tata Consultancy Services (TCS) in the upcoming week?
@@ -197,53 +240,6 @@ Culturally aware strategies include:
 - **Festival & Cultural Factors**: Insights into events like Diwali (Muhurat Trading), budget announcements, and investor sentiment.
 - **FII/DII Flow and Retail Behavior**: Specific guidance considering both institutional and retail dynamics.
 
-## Implementation
-
-### Quick Start
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-
-model = AutoModelForCausalLM.from_pretrained("bhaskartripathi/GPT_Neo_Market_Analysis")
-tokenizer = AutoTokenizer.from_pretrained("bhaskartripathi/GPT_Neo_Market_Analysis")
-
-input_text = '''[INST] Given the following stock market data and technical analysis:
-Stock: EXAMPLE
-Date: 2024-01-01
-Technical Analysis:
-Current Price: ₹100
-Daily Range: ₹98 - ₹102
-Trading Volume: 1,000,000
-RSI: 55
-MACD: Bullish
-Based on this technical analysis, what is the likely price movement for tomorrow and why? [/INST]'''
-
-inputs = tokenizer(input_text, return_tensors="pt")
-outputs = model.generate(**inputs, max_new_tokens=50)
-result = tokenizer.decode(outputs[0], skip_special_tokens=True)
-```
-
-## Training Details
-
-### Dataset and Fine-tuning
-- **Dataset**: Comprehensive dataset featuring 6 years of Indian market data.
-- **Method**: Fine-tuned using QLoRA (4-bit quantization) for optimal efficiency.
-- **Training Infrastructure**: Utilized an Nvidia T4 GPU, trained for ~6 hours with PEFT framework version 0.13.2.
-
-## Performance Metrics
-- **Pattern Recognition**: High accuracy in classical and advanced pattern detection in Indian markets.
-- **Sentiment Correlation**: Strong alignment with local market movements.
-- **Risk & Volatility Handling**: Reliable risk analysis in volatile market conditions.
-
-## Use Cases
-
-- **Automated Market Analysis**: Insight generation for Indian stock portfolios.
-- **Strategy Development**: Recommendations for traders in local markets.
-- **Risk Management**: Portfolio analysis and risk mitigation insights.
-- **Educational Utility**: Training tool for new traders learning about Indian markets.
-
-## Social Impact
-
-IndicFinGPT democratizes sophisticated AI-based financial analysis for the Indian stock market, providing affordable and accessible tools for both seasoned investors and new traders.
 
 ## Citation
 ```bibtex