Llama-3-Groq-70B-Tool-Use
| Property | Value |
|---|---|
| Parameter Count | 70.6B |
| License | Meta Llama 3 Community License |
| Architecture | Optimized Transformer |
| Tensor Type | BF16 |
| Language | English |
What is Llama-3-Groq-70B-Tool-Use?
Llama-3-Groq-70B-Tool-Use is a sophisticated language model specifically engineered for advanced tool use and function calling capabilities. Built upon Meta's Llama 3 70B base model, it has been fine-tuned using Direct Preference Optimization (DPO) to excel at tasks involving API interactions and structured data manipulation. The model has achieved an impressive 90.76% accuracy on the Berkeley Function Calling Leaderboard (BFCL), marking it as the top performer among open-source 70B LLMs.
Implementation Details
The model implements a carefully optimized transformer architecture with 70.6 billion parameters, utilizing BF16 tensor precision for efficient computation. It's designed with specific attention to temperature and top_p sampling configurations, with recommended starting values of temperature=0.5 and top_p=0.65.
- Full fine-tuning on Llama 3 70B base model
- Direct Preference Optimization for enhanced tool use capabilities
- Specialized function calling framework with XML-based tool definition support
- Optimized for structured API interactions and data manipulation
Core Capabilities
- Advanced function calling with structured JSON responses
- Tool use optimization with XML-based interface
- High accuracy in interpreting and executing API-like interactions
- Flexible parameter adjustment for various use cases
- Structured data manipulation and processing
Frequently Asked Questions
Q: What makes this model unique?
This model stands out due to its specialized optimization for tool use and function calling, achieving the highest accuracy (90.76%) among open-source 70B models on the BFCL. Its unique XML-based tool definition system and structured JSON response format make it particularly suitable for API interactions and automated tool use scenarios.
Q: What are the recommended use cases?
The model is ideal for applications requiring structured API interactions, function calling, and tool use scenarios. It's particularly well-suited for research and development in automated systems, API integrations, and complex data manipulation tasks. However, for general knowledge or open-ended tasks, a standard language model might be more appropriate.
