adonlee/LLaMA_2_13B_SFT_v0
adonlee/LLaMA_2_13B_SFT_v0 is a 13 billion parameter language model based on the LLaMA 2 architecture, fine-tuned for general instruction following. This model demonstrates competitive performance across various benchmarks, including ARC, HellaSwag, and MMLU, making it suitable for a range of natural language understanding and generation tasks. Its supervised fine-tuning (SFT) aims to enhance its ability to respond accurately and coherently to user prompts.
Loading preview...
Overview
adonlee/LLaMA_2_13B_SFT_v0 is a 13 billion parameter language model built upon the LLaMA 2 architecture, specifically enhanced through supervised fine-tuning (SFT). This model is designed to follow instructions effectively, providing coherent and relevant responses across a variety of general-purpose natural language tasks.
Key Capabilities & Performance
This model has been evaluated on the Open LLM Leaderboard, showcasing its performance across several key benchmarks:
- Average Score: 50.97
- ARC (25-shot): 62.03
- HellaSwag (10-shot): 83.8
- MMLU (5-shot): 58.39
- TruthfulQA (0-shot): 49.92
- Winogrande (5-shot): 77.27
- GSM8K (5-shot): 12.43
- DROP (3-shot): 12.96
These scores indicate its proficiency in common sense reasoning, reading comprehension, and general knowledge tasks, with a context length of 4096 tokens.
Good For
- General instruction-following applications.
- Tasks requiring common sense reasoning and factual recall.
- Prototyping and development where a LLaMA 2-based 13B model with SFT is desired.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.