Smaug-Llama-3-70B-Instruct
| Property | Value |
|---|---|
| Parameter Count | 70.6B |
| Base Model | Meta-Llama-3-70B-Instruct |
| License | LLaMA 3 License |
| Developer | Abacus.AI |
| Paper | Smaug Paper |
What is Smaug-Llama-3-70B-Instruct?
Smaug-Llama-3-70B-Instruct is an advanced language model built upon Meta's LLaMA 3 architecture, incorporating novel Smaug techniques to enhance performance in real-world multi-turn conversations. This model represents a significant improvement over the base LLaMA-3-70B-Instruct, achieving performance metrics that rival GPT-4-Turbo on various benchmarks.
Implementation Details
The model utilizes BF16 tensor types and maintains compatibility with the original LLaMA 3 prompt format. It's designed for efficient deployment using the Transformers library and can be easily integrated into existing workflows.
- Built on Meta's LLaMA 3 70B architecture
- Implements specialized Smaug optimization techniques
- Maintains original prompt format compatibility
- Supports flexible deployment options
Core Capabilities
- Top performance on Arena-Hard benchmark (56.7 score)
- Exceptional MT-Bench results (9.21 average score)
- Strong performance across multiple evaluation metrics (ARC, Hellaswag, MMLU)
- Enhanced multi-turn conversation capabilities
- Competitive performance with GPT-4-Turbo
Frequently Asked Questions
Q: What makes this model unique?
The model's distinctive feature is its implementation of Smaug techniques, which significantly improve its performance in real-world conversations while maintaining competitive scores across standard benchmarks. It's currently the top open-source model on Arena-Hard and performs nearly on par with Claude Opus.
Q: What are the recommended use cases?
The model excels in multi-turn conversations, complex reasoning tasks, and general instruction following. It's particularly well-suited for applications requiring human-like dialogue capabilities and sophisticated problem-solving abilities.
