Update README with correct repository structure and enhanced documentation

README.md

@@ -1,3 +1,138 @@
 ---
 license: apache-2.0
+base_model: allura-forge/Llama-3.3-8B-Instruct
+datasets:
+- TeichAI/claude-4.5-opus-high-reasoning-250x
+language:
+- en
+tags:
+- thinking
+- reasoning
+- instruct
+- economics
+- finance
+- analysis
+- llama3.3
+- unsloth
+- finetune
+- bfloat16
+- 128k context
+pipeline_tag: text-generation
+library_name: transformers
 ---
+
+# AEGIS Conduct - Economic Analysis Model
+
+<img src="econ/matrix-neo-reloaded-fight.gif" style="float:right; width:300px; height:300px; padding:10px;">
+
+## Model Overview
+
+This repository contains the Llama 3.3 8B Instruct model with thinking capabilities, fine-tuned for economic and financial analysis using Claude 4.5-Opus High Reasoning dataset.
+
+**Key Features:**
+- **Thinking Mode**: Automatic activation for complex reasoning
+- **Economic Focus**: Specialized for financial analysis and market insights  
+- **128k Context**: Extended context window for comprehensive analysis
+- **Optimized**: Fine-tuned with Unsloth for efficient inference
+
+## Model Details
+
+- **Base Model**: allura-forge/Llama-3.3-8B-Instruct  
+- **Fine-tuning Dataset**: TeichAI/claude-4.5-opus-high-reasoning-250x
+- **Context Length**: 128k tokens
+- **Training Method**: Unsloth (3 epochs)
+- **Format**: SafeTensors
+- **Precision**: bfloat16
+
+## Repository Structure
+
+The model files are organized in the econ/ directory:
+
+```
+econ/
+├── config.json                    # Model configuration
+├── generation_config.json         # Generation parameters
+├── tokenizer.json                 # Tokenizer vocabulary
+├── tokenizer_config.json          # Tokenizer configuration
+├── special_tokens_map.json        # Special tokens mapping
+├── chat_template.jinja            # Chat template
+├── model.safetensors.index.json   # Model index
+├── model-00001-of-00004.safetensors  # Model weights (part 1)
+├── model-00002-of-00004.safetensors  # Model weights (part 2)
+├── model-00003-of-00004.safetensors  # Model weights (part 3)
+├── model-00004-of-00004.safetensors  # Model weights (part 4)
+├── reco.py                        # Model utilities
+└── matrix-neo-reloaded-fight.gif  # Visual asset
+```
+
+## Usage
+
+### Quick Start with Transformers
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load model and tokenizer from econ subdirectory
+tokenizer = AutoTokenizer.from_pretrained("Gaston895/aegisconduct", subfolder="econ")
+model = AutoModelForCausalLM.from_pretrained("Gaston895/aegisconduct", subfolder="econ")
+
+# Generate response
+inputs = tokenizer("Analyze the economic impact of inflation on consumer spending:", return_tensors="pt")
+outputs = model.generate(**inputs, max_length=512, temperature=0.7)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+### Thinking Mode Activation
+
+The model automatically activates thinking mode for complex reasoning. Use prompts like:
+
+```python
+# These prompts will trigger thinking mode
+prompts = [
+    "Think deeply: Analyze the economic implications of rising interest rates",
+    "Explain the financial impact of supply chain disruptions",
+    "Think through: What are the long-term effects of quantitative easing?"
+]
+```
+
+### Recommended Settings
+
+- **Temperature**: 0.7
+- **Repetition Penalty**: 1.05  
+- **Top-p**: 0.95
+- **Min-p**: 0.05
+- **Top-k**: 40
+- **Context Window**: 4k minimum, 8k+ recommended
+
+## Capabilities
+
+This model excels at:
+
+- **Economic Analysis**: Market trends, policy impacts, forecasting
+- **Financial Planning**: Investment strategies, risk assessment
+- **Data Interpretation**: Economic indicators, statistical analysis  
+- **Policy Analysis**: Regulatory impacts, fiscal policy effects
+- **Global Economics**: International trade, currency analysis
+- **Research**: Academic-level economic reasoning and explanation
+
+## Example Outputs
+
+The model provides detailed, step-by-step reasoning for complex economic questions, often showing its "thinking" process before delivering final answers.
+
+## Technical Notes
+
+- Optimized for inference with various backends (transformers, llama.cpp, etc.)
+- Supports both instruct and thinking modes
+- No system prompt required (thinking tags self-generate)
+- Compatible with quantization (Q4KS, IQ3_M recommended minimum)
+
+## License
+
+Apache 2.0 (inherited from base model)
+
+## Credits
+
+- **Base Model**: [allura-forge/Llama-3.3-8B-Instruct](https://huggingface.co/allura-forge/Llama-3.3-8B-Instruct)
+- **Dataset**: [TeichAI/claude-4.5-opus-high-reasoning-250x](https://huggingface.co/datasets/TeichAI/claude-4.5-opus-high-reasoning-250x)
+- **Training Framework**: [Unsloth](https://github.com/unslothai/unsloth)