Update README.md

README.md

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----
-license: apache-2.0
-tags:
-- llama-factory
----
+### Nidum-Llama-3.2-3B-Uncensored  
+
+[![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)  
+**Explore Nidum's Open-Source Projects on GitHub**: [https://github.com/NidumAI-Inc](https://github.com/NidumAI-Inc)
+
+---
+
+### Welcome to Nidum!  
+At Nidum, we believe in pushing the boundaries of innovation by providing advanced and unrestricted AI models for every application. Dive into our world of possibilities and experience the freedom of **Nidum-Llama-3.2-3B-Uncensored**, tailored to meet diverse needs with exceptional performance.
+
+---
+
+### Key Features
+
+1. **Uncensored Responses**: Capable of addressing any query without content restrictions, offering detailed and uninhibited answers.
+2. **Versatility**: Excels in diverse use cases, from complex technical queries to engaging casual conversations.
+3. **Advanced Contextual Understanding**: Draws from an expansive knowledge base for accurate and context-aware outputs.
+4. **Extended Context Handling**: Optimized for handling long-context interactions for improved continuity and depth.
+5. **Customizability**: Adaptable to specific tasks and user preferences through fine-tuning.
+
+---
+
+### Use Cases
+
+- **Open-Ended Q&A**  
+- **Creative Writing and Ideation**  
+- **Research Assistance**  
+- **Educational Queries**  
+- **Casual Conversations**  
+- **Mathematical Problem Solving**  
+- **Long-Context Dialogues**  
+
+---
+
+### How to Use
+
+To start using **Nidum-Llama-3.2-3B-Uncensored**, follow the sample code below:
+
+```python
+import torch
+from transformers import pipeline
+
+pipe = pipeline(
+    "text-generation",
+    model="nidum/Nidum-Llama-3.2-3B-Uncensored",
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device="cuda",  # replace with "mps" to run on a Mac device
+)
+
+messages = [
+    {"role": "user", "content": "Tell me something fascinating."},
+]
+
+outputs = pipe(messages, max_new_tokens=256)
+assistant_response = outputs[0]["generated_text"][-1]["content"].strip()
+print(assistant_response)
+```
+
+---
+
+### Datasets and Fine-Tuning
+
+The following fine-tuning datasets are leveraged to enhance specific model capabilities:
+
+- **Uncensored Data**: Enables unrestricted and uninhibited responses.
+- **RAG-Based Fine-Tuning**: Optimizes retrieval-augmented generation for knowledge-intensive tasks.
+- **Long Context Fine-Tuning**: Enhances the model's ability to process and maintain coherence in extended conversations.
+- **Math-Instruct Data**: Specially curated for precise and contextually accurate mathematical reasoning.
+
+---
+
+### Benchmarks
+
+After fine-tuning with **uncensored data**, **Nidum-Llama-3.2-3B** demonstrates **superior performance compared to the original LLaMA model**, particularly in accuracy and handling diverse, unrestricted scenarios.
+
+#### GPQA: Evaluating Domain Expertise  
+We present **GPQA**, a challenging dataset of 448 multiple-choice questions written by domain experts in biology, physics, and chemistry.
+
+| **Category**                          | **Metric**                   | **LLaMA 3B** | **Nidum 3B** |
+|---------------------------------------|------------------------------|--------------|--------------|
+| **gpqa_diamond_cot_n_shot**           | Exact Match (Flexible)       | 0            | 0.2          |
+|                                       | Accuracy                     | 0.1          | 0.2          |
+| **gpqa_diamond_generative_n_shot**    | Exact Match (Flexible)       | 0.3          | 0.5          |
+| **gpqa_diamond_zeroshot**             | Accuracy                     | 0.2          | 0.3          |
+| **gpqa_extended_cot_n_shot**          | Exact Match (Flexible)       | 0.2          | 0            |
+| **gpqa_extended_cot_zeroshot**        | Exact Match (Flexible)       | 0.2          | 0.3          |
+| **gpqa_extended_generative_n_shot**   | Exact Match (Flexible)       | 0.1          | 0.2          |
+| **gpqa_extended_n_shot**              | Accuracy                     | 0.2          | 0.2          |
+| **gpqa_extended_zeroshot**            | Accuracy                     | 0.1          | 0.1          |
+| **gpqa_main_cot_n_shot**              | Exact Match (Flexible)       | 0            | 0.1          |
+| **gpqa_main_cot_zeroshot**            | Exact Match (Flexible)       | 0.2          | 0.2          |
+| **gpqa_main_generative_n_shot**       | Exact Match (Flexible)       | 0.2          | 0.2          |
+| **gpqa_main_n_shot**                  | Accuracy                     | 0.4          | 0.3          |
+| **gpqa_main_zeroshot**                | Accuracy                     | 0.3          | 0.4          |
+
+---
+
+#### HellaSwag: Common Sense Reasoning Benchmark  
+
+HellaSwag evaluates a language model's ability to reason using common sense through sentence completion tasks.
+
+| **Metric**                | **Llama 3B** | **Nidum 3B** |
+|---------------------------|--------------|--------------|
+| **hellaswag/acc**         | 0.3          | 0.4          |
+| **hellaswag/acc_norm**    | 0.3          | 0.4          |
+| **hellaswag/acc_norm_stderr** | 0.15275      | 0.1633       |
+| **hellaswag/acc_stderr**  | 0.15275      | 0.1633       |
+
+---
+
+### Contributing
+
+We welcome contributions to improve and extend the model’s capabilities. Stay tuned for updates on how to contribute.
+
+---
+
+### Contact
+
+For inquiries, collaborations, or further information, please reach out to us at **[email protected]**.
+
+---
+
+### Explore the Possibilities
+
+Dive into unrestricted creativity and innovation with **Nidum-Llama-3.2-3B-Uncensored**!