Llama-3.1-Tulu-3-405B
| Property | Value |
|---|---|
| Model Size | 405B parameters |
| License | Llama 3.1 Community License Agreement |
| Paper | Research Paper |
| Primary Language | English |
| Base Model | meta-llama/llama-3.1-405B |
What is Llama-3.1-Tulu-3-405B?
Llama-3.1-Tulu-3-405B is a state-of-the-art language model developed by Allen AI that represents the culmination of advanced instruction-following capabilities. Built on Meta's Llama 3.1 architecture, it has been extensively trained using a combination of publicly available, synthetic, and human-created datasets. The model excels particularly in mathematical reasoning, coding, and general instruction following tasks.
Implementation Details
The model implements a sophisticated training pipeline including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reward Learning through Value Ranking (RLVR). It uses a specialized chat template and can be easily deployed using popular frameworks like HuggingFace Transformers and VLLM.
- Advanced chat template with user/assistant formatting
- Comprehensive evaluation across multiple benchmarks
- Optimized hyperparameters for RLVR training
- Support for context length up to 8192 tokens
Core Capabilities
- Exceptional performance on MATH (67.3%) and GSM8K (95.5%) benchmarks
- Strong code generation abilities with 95.9% pass@10 on HumanEval
- Robust safety measures with 86.7% average score on safety tasks
- State-of-the-art instruction following capabilities (86.0% on IFEval)
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its balanced performance across various tasks, particularly excelling in mathematical reasoning and coding while maintaining strong safety measures. It's part of the fully open-source Tülu family, providing transparent training methodology and evaluation metrics.
Q: What are the recommended use cases?
The model is particularly well-suited for complex mathematical problem-solving, code generation, and general instruction following tasks. It's designed for research and educational use, with strong capabilities in both technical and general-purpose applications.
