Nidum Llama 3.2 3b Uncensored
1,090 Pulls Updated 5 weeks ago
Updated 5 weeks ago
5 weeks ago
b6eb9504fae4 · 2.3GB
Readme
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!