Update README.md

README.md

@@ -1,22 +1,129 @@
 ---
-base_model: meta-llama/Llama-3.1-8B-Instruct
+base_model:
+- Meta/LLama3.1-8B-Instruct
 tags:
 - text-generation-inference
 - transformers
 - unsloth
-- llama
+- Llama3
 - trl
+- COT
+- Reasoning
 license: apache-2.0
 language:
 - en
+datasets:
+- Daemontatox/LongCOT-Reason
+metrics:
+- accuracy
+- character
+- competition_math
+- code_eval
+library_name: transformers
+new_version: Daemontatox/AetherLlama
 ---
 
-# Uploaded  model
+![image](./image.webp)
 
-- **Developed by:** Daemontatox
-- **License:** apache-2.0
-- **Finetuned from model :** meta-llama/Llama-3.1-8B-Instruct
+# AetherLlama   
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+- **Developed by:** Daemontatox  
+- **License:** Apache 2.0   
+- **Finetuned Using:** [Unsloth](https://github.com/unslothai/unsloth), Hugging Face Transformers, and TRL Library  
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+## 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.  
+
+---
+
+## 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.