Llama-3.1-Tulu-3-8B
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| License | Llama 3.1 Community License |
| Research Paper | arXiv:2411.15124 |
| Base Model | Llama-3.1-Tulu-3-8B-DPO |
| Tensor Type | BF16 |
What is Llama-3.1-Tulu-3-8B?
Llama-3.1-Tulu-3-8B is a state-of-the-art instruction-following language model developed by Allen Institute for AI. It represents a significant advancement in open-source AI, specifically designed to excel at diverse tasks including mathematical reasoning, problem-solving, and conversational abilities. Built upon the Llama 3.1 architecture, this model has been enhanced through a sophisticated training process involving SFT (Supervised Fine-Tuning), DPO (Direct Preference Optimization), and RLVR techniques.
Implementation Details
The model implements a sophisticated architecture with several key technical features:
- 8.03 billion parameters optimized for efficient processing
- Utilizes BF16 tensor format for improved computational efficiency
- Implements a specialized chat template for structured conversation handling
- Supports both standard inference and VLLM serving capabilities
- Maximum context length of 8192 tokens
Core Capabilities
- Exceptional performance on mathematical tasks (87.6% on GSM8K)
- Strong reasoning capabilities demonstrated through BigBench Hard tasks
- Robust instruction following with 82.4% on IFEval
- Impressive code generation abilities (83.9% pass@10 on HumanEval)
- Enhanced safety features with 85.5% average on safety tasks
Frequently Asked Questions
Q: What makes this model unique?
Tulu-3 stands out for its balanced performance across diverse tasks, particularly excelling in mathematical reasoning and instruction following while maintaining strong safety standards. It's fully open-source with documented training procedures, making it valuable for both research and practical applications.
Q: What are the recommended use cases?
The model is particularly well-suited for mathematical problem-solving, coding tasks, general instruction following, and conversational applications. It's designed for research and educational use, with specific strengths in technical and analytical tasks while maintaining high safety standards.
