| ---
|
| license: apache-2.0
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| base_model: allura-forge/Llama-3.3-8B-Instruct
|
| datasets:
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| - TeichAI/claude-4.5-opus-high-reasoning-250x
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| language:
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| - en
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| tags:
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| - thinking
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| - reasoning
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| - instruct
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| - economics
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| - finance
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| - analysis
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| - llama3.3
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| - unsloth
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| - finetune
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| - bfloat16
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| - 128k context
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| pipeline_tag: text-generation
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| library_name: transformers
|
| ---
|
|
|
| # AEGIS Conduct - Economic Analysis Model
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|
|
| ## Model Overview
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|
|
| 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.
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|
|
| **Key Features:**
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| - **Thinking Mode**: Automatic activation for complex reasoning
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| - **Economic Focus**: Specialized for financial analysis and market insights
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| - **128k Context**: Extended context window for comprehensive analysis
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| - **Optimized**: Fine-tuned with Unsloth for efficient inference
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|
|
| ## Model Details
|
|
|
| - **Base Model**: allura-forge/Llama-3.3-8B-Instruct
|
| - **Fine-tuning Dataset**: TeichAI/claude-4.5-opus-high-reasoning-250x
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| - **Context Length**: 128k tokens
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| - **Training Method**: Unsloth (3 epochs)
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| - **Format**: SafeTensors
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| - **Precision**: bfloat16
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|
|
| ## Repository Structure
|
|
|
| Configuration files are in the root directory, with model weights in the econ subdirectory:
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|
|
| ```
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| ├── config.json # Model configuration
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| ├── generation_config.json # Generation parameters
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| ├── tokenizer_config.json # Tokenizer configuration
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| ├── special_tokens_map.json # Special tokens mapping
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| ├── tokenizer.json # Tokenizer vocabulary
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| ├── model.safetensors.index.json # Model index
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| ├── chat_template.jinja # Chat template
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| ├── matrix-neo-reloaded-fight.gif # Visual asset
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| ├── README.md # This file
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| └── econ/
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| ├── model-00001-of-00004.safetensors # Model weights (part 1)
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| ├── model-00002-of-00004.safetensors # Model weights (part 2)
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| ├── model-00003-of-00004.safetensors # Model weights (part 3)
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| └── model-00004-of-00004.safetensors # Model weights (part 4)
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| ```
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|
|
| ## Usage
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|
|
| ### Loading the Model
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|
|
| ```python
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| from transformers import AutoTokenizer, AutoModelForCausalLM
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|
|
| # Method 1: Load with subfolder for model weights
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| tokenizer = AutoTokenizer.from_pretrained("Gaston895/aegisconduct")
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| model = AutoModelForCausalLM.from_pretrained("Gaston895/aegisconduct", subfolder="econ")
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|
|
| # Method 2: If all files are at root (after full migration)
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| # tokenizer = AutoTokenizer.from_pretrained("Gaston895/aegisconduct")
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| # model = AutoModelForCausalLM.from_pretrained("Gaston895/aegisconduct")
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| ```
|
|
|
| ### Generate Response
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|
|
| ```python
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| # Generate response
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| inputs = tokenizer("Analyze the economic impact of inflation on consumer spending:", return_tensors="pt")
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| outputs = model.generate(**inputs, max_length=512, temperature=0.7)
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| response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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| print(response)
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| ```
|
|
|
| ### Thinking Mode Activation
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|
|
| The model automatically activates thinking mode for complex reasoning:
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|
|
| ```python
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| # These prompts will trigger thinking mode
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| prompts = [
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| "Think deeply: Analyze the economic implications of rising interest rates",
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| "Explain the financial impact of supply chain disruptions",
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| "Think through: What are the long-term effects of quantitative easing?"
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| ]
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| ```
|
|
|
| ### Recommended Settings
|
|
|
| - **Temperature**: 0.7
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| - **Repetition Penalty**: 1.05
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| - **Top-p**: 0.95
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| - **Min-p**: 0.05
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| - **Top-k**: 40
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| - **Context Window**: 4k minimum, 8k+ recommended
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|
|
| ## Capabilities
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|
|
| This model excels at:
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|
|
| - **Economic Analysis**: Market trends, policy impacts, forecasting
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| - **Financial Planning**: Investment strategies, risk assessment
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| - **Data Interpretation**: Economic indicators, statistical analysis
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| - **Policy Analysis**: Regulatory impacts, fiscal policy effects
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| - **Global Economics**: International trade, currency analysis
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| - **Research**: Academic-level economic reasoning and explanation
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|
|
| ## Technical Notes
|
|
|
| - Configuration files are at root level for easy access
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| - Model weights are in the `econ/` subdirectory
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| - Use `subfolder="econ"` when loading model weights
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| - Supports both instruct and thinking modes
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| - No system prompt required (thinking tags self-generate)
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| - Compatible with quantization (Q4KS, IQ3_M recommended minimum)
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|
|
| ## License
|
|
|
| Apache 2.0 (inherited from base model)
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|
|
| ## Credits
|
|
|
| - **Base Model**: [allura-forge/Llama-3.3-8B-Instruct](https://huggingface.co/allura-forge/Llama-3.3-8B-Instruct)
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| - **Dataset**: [TeichAI/claude-4.5-opus-high-reasoning-250x](https://huggingface.co/datasets/TeichAI/claude-4.5-opus-high-reasoning-250x)
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| - **Training Framework**: [Unsloth](https://github.com/unslothai/unsloth)
|
| |
