transformers pytorch safetensors llama text-generation text-generation-inference unsloth Llama3 trl COT Reasoning conversational en dataset:Daemontatox/LongCOT-Reason license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model:
- Meta/LLama3.1-8B-Instruct
datasets:
- Daemontatox/LongCOT-Reason
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- character
- competition_math
- code_eval
pipeline_tag: text-generation
tags:
- text-generation-inference
- transformers
- unsloth
- Llama3
- trl
- COT
- Reasoning
new_version: Daemontatox/AetherLlama
---

![image](./image.webp)

# AetherLlama   

- **Developed by:** Daemontatox  
- **License:** Apache 2.0   
- **Finetuned Using:** [Unsloth](https://github.com/unslothai/unsloth), Hugging Face Transformers, and TRL Library  

## Model Overview  

The **  AetherLlama  Model** is an advanced AI system optimized for logical reasoning, multi-step problem-solving, and decision-making tasks. Designed with efficiency and accuracy in mind, it employs a structured system prompt to ensure high-quality answers through a transparent and iterative thought process.  

### System Prompt and Workflow  

This model operates using an innovative reasoning framework structured around the following steps:  

1. **Initial Thought:**  
   The model uses `<Thinking>` tags to reason step-by-step and craft its best possible response.  
   Example:  

2. **Self-Critique:**  
It evaluates its initial response within `<Critique>` tags, focusing on:  
- **Accuracy:** Is it factually correct and verifiable?  
- **Clarity:** Is it clear and free of ambiguity?  
- **Completeness:** Does it fully address the request?  
- **Improvement:** What can be enhanced?  
Example:  

3. **Revision:**  
Based on the critique, the model refines its response within `<Revising>` tags.  
Example:  

4. **Final Response:**  
The revised response is presented clearly within `<Final>` tags.  
Example:  

5. **Tag Innovation:**  
When needed, the model creates and defines new tags for better structuring or clarity, ensuring consistent usage.  
Example:  

### Key Features  
- **Structured Reasoning:** Transparent, multi-step approach for generating and refining answers.  
- **Self-Improvement:** Built-in critique and revision ensure continuous response enhancement.  
- **Clarity and Adaptability:** Tagging system provides organized, adaptable responses tailored to user needs.  
- **Creative Flexibility:** Supports dynamic problem-solving with the ability to introduce new tags and concepts.  

---

## Use Cases  

The model is designed for various domains, including:  
1. **Research and Analysis:** Extracting insights and providing structured explanations.  
2. **Education:** Assisting with tutoring by breaking down complex problems step-by-step.  
3. **Problem-Solving:** Offering logical and actionable solutions for multi-step challenges.  
4. **Content Generation:** Producing clear, well-organized creative or professional content.  

---

## Training Details  

- **Frameworks:**  
- [Unsloth](https://github.com/unslothai/unsloth) for accelerated training.  
- Hugging Face Transformers and the TRL library for reinforcement learning with human feedback (RLHF).  

- **Dataset:** Finetuned on diverse reasoning-focused tasks, including logical puzzles, mathematical problems, and commonsense reasoning scenarios.  

- **Hardware Efficiency:**  
- Trained with bnb-4bit precision for reduced memory usage.  
- Optimized training pipeline achieving 2x faster development cycles.  

---

## Performance Metrics  

The model excels in reasoning benchmarks:  
- **ARC (AI2 Reasoning Challenge):** High accuracy in logical and commonsense tasks.  
- **GSM8K (Math Reasoning):** Superior results in multi-step problem-solving.  
- **CommonsenseQA:** Strong comprehension of everyday reasoning tasks.  

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## Ethical Considerations  

- **Transparency:** Responses are structured for verifiability through tagging.  
- **Bias Mitigation:** Includes self-critique to minimize biases and ensure fairness.  
- **Safe Deployment:** Users are encouraged to evaluate outputs to prevent harm or misinformation.  

---

## License  

This model is distributed under the Apache 2.0 license, allowing users to use, modify, and share it in compliance with the license terms.  

---

## Acknowledgments  

Special thanks to:  
- [Unsloth](https://github.com/unslothai/unsloth) for accelerated training workflows.  
- Hugging Face for their powerful tools and libraries.  

---

Experience the **AetherLlama l**, leveraging its structured reasoning and self-improvement capabilities for any task requiring advanced AI reasoning.