Secbone/llama-2-13B-instructed: An Instruction-Finetuned Llama 2 Model

This model, developed by Secbone, is an instruction-finetuned variant of the Llama 2 13B parameter model. It is designed to follow instructions effectively, making it suitable for a wide range of natural language processing tasks. The model's performance has been evaluated on the Open LLM Leaderboard, showcasing its capabilities across several key metrics.

Key Capabilities & Performance

The Secbone/llama-2-13B-instructed model achieves an average score of 47.84 on the Open LLM Leaderboard. Specific benchmark results highlight its strengths:

• ARC (25-shot): 59.39
• HellaSwag (10-shot): 83.88
• MMLU (5-shot): 55.57
• TruthfulQA (0-shot): 46.89
• Winogrande (5-shot): 74.03

While demonstrating solid performance in general reasoning and common sense tasks, its scores on more complex reasoning benchmarks like GSM8K (8.04) and DROP (7.06) indicate areas for potential further optimization.

Good For

• General-purpose conversational AI and chatbots.
• Tasks requiring instruction following and text generation.
• Applications where a 13 billion parameter model offers a balance between performance and computational resources.