qwen2_stock

📈 Qwen2 Stock Analysis SLM (GGUF)

Welcome to the Qwen2 Stock Analysis SLM, a fine-tuned Small Language Model (SLM) based on the Qwen-7B architecture. This model has been specifically optimized to perform technical stock market analysis, with a particular focus on Indian stock market indicators.

By leveraging Unsloth and QLoRA, this model has been trained to interpret technical data such as Price, Relative Strength Index (RSI), and Moving Average Convergence Divergence (MACD) to generate concise, actionable momentum summaries.

---

📊 Model Details

---

🎯 Intended Use

This model is designed for developers, quantitative analysts, and financial enthusiasts who want to run a lightweight, local AI model to interpret stock data.

Primary Capabilities:

• Summarizing a stock's technical status based on Price and RSI.
• Analyzing MACD momentum and identifying potential trend reversals.
• Operating entirely locally via GGUF for maximum privacy and low latency.

⚠️ Disclaimer: This model is for educational and informational purposes only. It does not provide financial advice. Always conduct your own research or consult a certified financial advisor before making investment decisions.

---

⚙️ Training Details

The model was efficiently fine-tuned using a synthetic dataset tailored to Indian stock market technical indicators.

• Training Method: QLoRA (Rank 16)
• Framework: Unsloth
• Epochs: 15
• Steps: 60
• Quantization: 4-bit (bitsandbytes) during training, subsequently merged and exported to Q4_K_M GGUF for highly optimized CPU/GPU inference.

---

🚀 How to Use (Local Inference)

Because this model is provided in the GGUF format, it is highly accessible and can be run on consumer hardware using popular local AI inference engines.

1. llama.cpp

You can run this model directly in your terminal using llama.cpp. Once you have downloaded the .gguf file, use the following command:

./llama-cli --model qwen2_stock_analysis.Q4_K_M.gguf --prompt "### Instruction:\nSummarize the technical status for HDFC\n\n### Input:\nPrice: 1650.00, RSI: 78.50\n\n### Response:\n"