Financial GPT-OSS 20B Q8 - Quantized Financial Analysis Model
Model Description
This is a quantized Q8_0 GGUF version of a fine-tuned financial analysis model based on GPT-OSS 20B. The model has been specialized for financial market analysis, providing technical analysis, risk assessments, trading signals, and price forecasts for various securities.
Model Details
Base Model: GPT-OSS 20B (unsloth/gpt-oss-20b-unsloth-bnb-4bit)
Fine-tuning Method: LoRA (Low-Rank Adaptation)
Quantization: Q8_0 GGUF format for efficient inference
Model Size: 12.1 GB (quantized from ~40GB original)
Context Length: 131,072 tokens
Architecture: Mixture of Experts (MoE) with 32 experts, 4 active
Training Data
The model was fine-tuned on 22,250 financial conversation pairs covering:
Institutional Signals: Volume and momentum-based institutional activity indicators
Usage Examples
Risk Assessment Query
User: "Can you assess the risk level for AAPL?"
Model Response:
Risk Assessment for AAPL:
**Overall Risk Level: Low**
**Volatility Analysis:**
- Daily volatility: 0.27%
- Sector: tech (High volatility)
**Technical Risks:**
- RSI at 44.53: Neutral positioning
- Trend strength: Moderate
**Key Risk Factors:**
1. Market correlation risk
2. Sector-specific headwinds
3. Technical resistance at $146.89
4. Support breakdown below $132.90
**Risk Mitigation:**
- Position sizing: Limit to 2-3% of portfolio
- Use stop-loss orders
- Consider hedging strategies
Trading Signal Query
User: "Should I buy or sell AAPL?"
Model Response:
Trading Signal for AAPL: **BUY**
Current Price: $147.79
Daily Change: -0.35%
**Signal Rationale:**
- MACD crossed above signal line
- RSI at 59.12 indicates neutral momentum
- Price is above 20-day SMA ($144.40)
**Risk Management:**
- Entry: $147.79
- Stop Loss: $140.40 (-5%)
- Target: $162.56 (+10%)
- Risk/Reward Ratio: 1:2
Note: This is technical analysis only. Consider fundamental factors and your risk tolerance.
Model Performance
Training Epochs: 1000 steps with checkpoints at 250, 500, 750, and 1000
Architecture: Leverages MoE efficiency with 32 experts, 4 active per token
Optimization: LoRA fine-tuning preserves base model capabilities while adding financial expertise
Quantization: Q8_0 maintains model quality while reducing inference requirements
Technical Specifications
Model Type: Causal Language Model (Financial Analysis Specialist)
Embedding Dimension: 2,880
Feed Forward Dimension: 2,880
Attention Heads: 64 (8 key-value heads)
RoPE Theta: 150,000
Vocabulary Size: 201,088 tokens
Quantization Method: Q8_0 with MXFP4 expert weights
Limitations and Disclaimers
⚠️ Important Financial Disclaimer
Not Financial Advice: This model provides technical analysis and educational content only. It is not licensed financial advice.
Risk Warning:
All trading involves risk of loss
Past performance does not guarantee future results
Consider your risk tolerance and investment objectives
Technical Limitations:
Based on technical analysis patterns only
Does not incorporate fundamental analysis
May not reflect real-time market conditions
Training data has a specific time cutoff
Model Limitations:
Responses are generated, not real-time analysis
No access to current market data during inference
Should be used as one input among many in decision-making
Usage Recommendations
Combine with Other Analysis: Use alongside fundamental analysis, news, and current market conditions
