nlpguy/Hermes-low-tune-3
nlpguy/Hermes-low-tune-3 is a 7 billion parameter language model created by nlpguy, merged using the SLERP method from nlpguy/Hermes-low-tune-2 and openaccess-ai-collective/DPOpenHermes-7B-v2. This model features a 4096-token context length and demonstrates strong general performance across various benchmarks, including an average score of 69.25 on the Open LLM Leaderboard. It is suitable for general-purpose language understanding and generation tasks.
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Model Overview
nlpguy/Hermes-low-tune-3 is a 7 billion parameter language model developed by nlpguy. It was created by merging two pre-trained models, nlpguy/Hermes-low-tune-2 and openaccess-ai-collective/DPOpenHermes-7B-v2, using the SLERP merge method via mergekit.
Performance Highlights
This model has been evaluated on the Open LLM Leaderboard, achieving a competitive average score of 69.25. Key benchmark results include:
- AI2 Reasoning Challenge (25-Shot): 66.21
- HellaSwag (10-Shot): 84.99
- MMLU (5-Shot): 63.74
- TruthfulQA (0-shot): 57.94
- Winogrande (5-shot): 78.77
- GSM8k (5-shot): 63.84
Detailed evaluation results are available here.
Use Cases
Given its balanced performance across various reasoning and language understanding tasks, Hermes-low-tune-3 is well-suited for a range of general-purpose applications requiring robust language capabilities, such as:
- Text generation
- Question answering
- Summarization
- Reasoning tasks