Nidum-Llama-3.2-3B-Uncensored

Explore Nidum’s Open-Source Projects on GitHub: https://github.com/NidumAI-Inc

Welcome to Nidum, where innovation meets limitless potential. With Nidum-Llama-3.2-3B-Uncensored, we redefine AI capabilities by offering advanced, unrestricted, and adaptable solutions for diverse applications.

🚀 Key Features

Unrestricted Responses
Delivers uninhibited and detailed answers, handling any topic or query.
Versatility
Excels in various tasks, including technical problem-solving, creative writing, and casual conversations.
Advanced Contextual Understanding
Powered by a robust knowledge base for accurate, context-aware interactions.
Extended Context Handling
Optimized to maintain coherence and depth in long, complex dialogues.
Customizability
Easily adaptable to specific use cases and user preferences through fine-tuning.

🛠️ Applications

Open-Ended Q&A
Creative Writing & Ideation
Research Assistance
Educational Support
Mathematical Problem-Solving
Casual Conversations
Long-Context Dialogues

💻 Getting Started

Here’s how to integrate Nidum-Llama-3.2-3B-Uncensored into your project:

from ollama import chat
from ollama import ChatResponse

# Example usage
response: ChatResponse = chat(model='llama3.2', messages=[
  {
    'role': 'user',
    'content': 'Why is the sky blue?',
  },
])

# Print response
print(response['message']['content'])

# Or access fields directly
print(response.message.content)

📊 Performance Benchmarks

Fine-tuned on uncensored data, Nidum-Llama-3.2-3B-Uncensored consistently outperforms the original LLaMA model in key benchmarks:

Benchmark	Metric	LLaMA 3B	Nidum 3B	Key Insights
GPQA	Exact Match	0.3	0.5	Significant improvement in generative and zero-shot tasks.
	Accuracy	0.4	0.5	Consistently better in knowledge-intensive scenarios.
HellaSwag	Accuracy	0.3	0.4	Enhanced common-sense reasoning and context prediction.

🔧 Fine-Tuning Datasets

Our model’s performance is enhanced by leveraging curated datasets:

Uncensored Data: Enables unrestricted and open-ended responses.
RAG-Based Fine-Tuning: Optimizes knowledge-intensive generation.
Long Context Fine-Tuning: Improves coherence in extended dialogues.
Math-Instruct Data: Refines precision in mathematical reasoning.

🤝 Contributing

We welcome contributions to further enhance Nidum-Llama-3.2-3B-Uncensored. Explore our open-source projects on GitHub.

📬 Contact

For inquiries, collaborations, or support, email us at info@nidum.ai.

🌟 Explore the Possibilities

Unleash your creativity and tackle challenges with Nidum-Llama-3.2-3B-Uncensored—your ultimate tool for innovation and exploration!