Update README.md

README.md

@@ -13,28 +13,136 @@ tags:
 pipeline_tag: text-generation
 ---
 
-# nidum/Nidum-Llama-3.2-3B-Uncensored-MLX-8bit
+### **Nidum-Llama-3.2-3B-Uncensored-MLX-8bit**  
 
-The Model [nidum/Nidum-Llama-3.2-3B-Uncensored-MLX-8bit](https://huggingface.co/nidum/Nidum-Llama-3.2-3B-Uncensored-MLX-8bit) was converted to MLX format from [nidum/Nidum-Llama-3.2-3B-Uncensored](https://huggingface.co/nidum/Nidum-Llama-3.2-3B-Uncensored) using mlx-lm version **0.19.2**.
+### **Welcome to Nidum!**  
+At Nidum, our mission is to bring cutting-edge AI capabilities to everyone with unrestricted access to innovation. With **Nidum-Llama-3.2-3B-Uncensored-MLX-8bit**, you get an optimized, efficient, and versatile AI model for diverse applications.  
 
-## Use with mlx
+---
+
+[![GitHub Icon](https://upload.wikimedia.org/wikipedia/commons/thumb/9/95/Font_Awesome_5_brands_github.svg/232px-Font_Awesome_5_brands_github.svg.png)](https://github.com/NidumAI-Inc)  
+**Discover Nidum's Open-Source Projects on GitHub**: [https://github.com/NidumAI-Inc](https://github.com/NidumAI-Inc)  
+
+---
+
+### **Key Features**
+
+1. **Efficient and Compact**: Developed in **MLX-8bit format** for improved performance and reduced memory demands.  
+2. **Wide Applicability**: Suitable for technical problem-solving, educational content, and conversational tasks.  
+3. **Advanced Context Awareness**: Handles long-context conversations with exceptional coherence.  
+4. **Streamlined Integration**: Optimized for use with the **mlx-lm library** for effortless development.  
+5. **Unrestricted Responses**: Offers uncensored answers across all supported domains.  
+
+---
+
+### **How to Use**
+
+To use **Nidum-Llama-3.2-3B-Uncensored-MLX-8bit**, install the **mlx-lm** library and follow these steps:
+
+#### **Installation**
 
 ```bash
 pip install mlx-lm
 ```
 
+#### **Usage**
+
 ```python
 from mlx_lm import load, generate
 
+# Load the model and tokenizer
 model, tokenizer = load("nidum/Nidum-Llama-3.2-3B-Uncensored-MLX-8bit")
 
-prompt="hello"
+# Create a prompt
+prompt = "hello"
 
+# Apply the chat template if available
 if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
     messages = [{"role": "user", "content": prompt}]
     prompt = tokenizer.apply_chat_template(
         messages, tokenize=False, add_generation_prompt=True
     )
 
+# Generate the response
 response = generate(model, tokenizer, prompt=prompt, verbose=True)
+
+# Print the response
+print(response)
 ```
+
+---
+
+### **About the Model**
+
+The **nidum/Nidum-Llama-3.2-3B-Uncensored-MLX-8bit** model, converted using **mlx-lm version 0.19.2**, brings:  
+
+- **Memory Efficiency**: Tailored for systems with limited hardware.  
+- **Performance Optimization**: Matches the capabilities of the original model while delivering faster inference.  
+- **Plug-and-Play**: Easily integrates with the **mlx-lm** library for deployment ease.  
+
+---
+
+### **Use Cases**
+
+- **Problem Solving in Tech and Science**  
+- **Educational and Research Assistance**  
+- **Creative Writing and Brainstorming**  
+- **Extended Dialogues**  
+- **Uninhibited Knowledge Exploration**  
+
+---
+
+### **Datasets and Fine-Tuning**  
+
+Derived from **Nidum-Llama-3.2-3B-Uncensored**, the MLX-8bit version inherits:  
+
+- **Uncensored Fine-Tuning**: Delivers detailed and open-ended responses.  
+- **RAG-Based Optimization**: Enhances retrieval-augmented generation for data-driven tasks.  
+- **Math Reasoning Support**: Precise mathematical computations and explanations.  
+- **Long-Context Training**: Ensures relevance and coherence in extended conversations.  
+
+---
+
+### **Quantized Model Download**  
+
+The **MLX-8bit** format strikes the perfect balance between memory optimization and performance.  
+
+---
+
+#### **Benchmark**
+
+| **Benchmark**    | **Metric**                       | **LLaMA 3B** | **Nidum 3B** | **Observation**                                                                                     |
+|-------------------|-----------------------------------|--------------|--------------|-----------------------------------------------------------------------------------------------------|
+| **GPQA**         | Exact Match (Flexible)           | 0.3          | 0.5          | Nidum 3B achieves notable improvement in **generative tasks**.                                      |
+|                  | Accuracy                         | 0.4          | 0.5          | Demonstrates strong performance, especially in **zero-shot** tasks.                                 |
+| **HellaSwag**    | Accuracy                         | 0.3          | 0.4          | Excels in **common-sense reasoning** tasks.                                                         |
+|                  | Normalized Accuracy              | 0.3          | 0.4          | Strong contextual understanding in sentence completion tasks.                                       |
+|                  | Normalized Accuracy (Stderr)     | 0.15275      | 0.1633       | Enhanced consistency in normalized accuracy.                                                        |
+|                  | Accuracy (Stderr)                | 0.15275      | 0.1633       | Demonstrates robustness in reasoning accuracy compared to LLaMA 3B.                                 |
+
+---
+
+### **Insights**
+
+1. **High Performance, Low Resource**: The MLX-8bit format is ideal for environments with limited memory and processing power.  
+2. **Seamless Integration**: Designed for smooth integration into lightweight systems and workflows.  
+
+---
+
+### **Contributing**  
+
+Join us in enhancing the **MLX-8bit** model's capabilities. Contact us for collaboration opportunities.  
+
+---
+
+### **Contact**  
+
+For questions, support, or feedback, email **info@nidum.ai**.  
+
+---
+
+### **Experience the Future**  
+
+Harness the power of **Nidum-Llama-3.2-3B-Uncensored-MLX-8bit** for a perfect blend of performance and efficiency.  
+
+---