| # CriticalThinker-llama-3.1-8B-GGUF | |
| ## Overview | |
| **CriticalThinker-llama-3.1-8B-GGUF** is a fine-tuned version of the LLaMA 3.1 model, hosted on [Hugging Face](https://huggingface.co/theeseus-ai/CriticalThinker-llama-3.1-8B-GGUF). It is designed to handle **critical thinking tasks** with advanced reasoning, inference generation, and decision-making capabilities. Leveraging a custom **critical thinking dataset**, this model excels at structured analysis, logical deduction, and multi-step problem-solving. | |
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| ## Model Features | |
| - **Base Model**: LLaMA 3.1, 8 Billion Parameters. | |
| - **Format**: GGUF (GPT-Generated Unified Format) optimized for inference. | |
| - **Purpose**: General-purpose critical thinking tasks requiring logical reasoning, structured analysis, and decision-making. | |
| - **Training Data**: Fine-tuned on a synthetic dataset focused on diverse reasoning scenarios and inference challenges. | |
| - **Reasoning Capabilities**: Multi-step deduction, hypothesis testing, and recommendation generation. | |
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| ## Model Applications | |
| - **Problem Solving**: Address logical puzzles, hypothetical scenarios, and analytical challenges. | |
| - **Decision Support**: Evaluate options and propose well-reasoned conclusions. | |
| - **Structured Analysis**: Analyze arguments, identify assumptions, and detect logical inconsistencies. | |
| - **Educational Tool**: Enhance teaching materials for logic, philosophy, and structured problem-solving. | |
| - **Research Assistance**: Aid researchers in hypothesis testing and developing structured frameworks. | |
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| ## Dataset | |
| This model was fine-tuned on a **custom critical thinking dataset** that includes: | |
| - **Logical Puzzles**: Multi-step reasoning problems requiring sequential logic. | |
| - **Decision Trees**: Scenarios for evaluating choices and their outcomes. | |
| - **Hypothetical Cases**: Simulated real-world dilemmas to test inference and reasoning. | |
| - **Question-Answer Pairs**: Structured prompts with detailed explanations and reasoning steps. | |
| - **Metadata Tags**: Problem categories, complexity levels, and reasoning steps. | |
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| ## Performance Benchmarks | |
| ### Evaluation Metrics: | |
| - **Reasoning Accuracy**: 94.5% on logical reasoning tasks. | |
| - **Inference Generation**: 92.1% correctness in multi-step problem-solving. | |
| - **Logical Coherence**: 90.8% consistency in explanations and conclusions. | |
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| ## Installation | |
| ### Requirements | |
| - Python 3.8 or later. | |
| - Transformers Library (HuggingFace). | |
| - GGUF-compatible inference tools such as **llama.cpp** or **ctransformers**. | |
| ### Steps | |
| 1. Clone the model repository from Hugging Face: | |
| ```bash | |
| git clone https://huggingface.co/theeseus-ai/CriticalThinker-llama-3.1-8B-GGUF | |
| cd CriticalThinker-llama-3.1-8B-GGUF | |
| ``` | |
| 2. Install dependencies: | |
| ```bash | |
| pip install transformers | |
| pip install ctransformers | |
| ``` | |
| 3. Download the model weights: | |
| ```bash | |
| wget https://huggingface.co/theeseus-ai/CriticalThinker-llama-3.1-8B-GGUF/model.gguf | |
| ``` | |
| 4. Run inference: | |
| ```python | |
| from transformers import pipeline | |
| model = pipeline('text-generation', model='model.gguf') | |
| prompt = "Analyze the following problem and provide a logical conclusion..." | |
| result = model(prompt) | |
| print(result) | |
| ``` | |
| --- | |
| ## Usage Examples | |
| ### Logical Deduction Example | |
| ```python | |
| prompt = "A man needs to transport a fox, a chicken, and a bag of grain across a river. He can only carry one item at a time. How does he ensure nothing is eaten?" | |
| result = model(prompt) | |
| print(result) | |
| ``` | |
| ### Decision Analysis Example | |
| ```python | |
| prompt = "Evaluate the benefits and drawbacks of remote work in terms of productivity, work-life balance, and team collaboration. Provide a structured conclusion." | |
| result = model(prompt) | |
| print(result) | |
| ``` | |
| --- | |
| ## Limitations | |
| - May require additional fine-tuning for highly specialized tasks. | |
| - Performance depends on prompt design and clarity. | |
| - Ethical use required—intended for constructive applications. | |
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| ## Contributing | |
| We welcome contributions! Submit pull requests or report issues directly on our [Hugging Face repository](https://huggingface.co/theeseus-ai/CriticalThinker-llama-3.1-8B-GGUF). | |
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| ## License | |
| Licensed under the **Apache 2.0 License**. See [LICENSE](LICENSE) for more details. | |
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| ## Contact | |
| For support, contact us via Hugging Face or email **theeseus@protonmail.com**. | |