Kukedlc/NeuralMaxime-7B-slerp
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Feb 18, 2024License:apache-2.0Architecture:Transformer0.0K Open Weights Cold
Kukedlc/NeuralMaxime-7B-slerp is a 7 billion parameter language model created by Kukedlc, resulting from a slerp merge of mlabonne/AlphaMonarch-7B and mlabonne/NeuralMonarch-7B. This model demonstrates strong general reasoning capabilities, achieving an average score of 76.17 on the Open LLM Leaderboard. It is suitable for a variety of natural language processing tasks, particularly those requiring robust reasoning and comprehension.
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Overview
Kukedlc/NeuralMaxime-7B-slerp is a 7 billion parameter language model developed by Kukedlc. It is a product of a slerp merge using LazyMergekit, combining the strengths of two base models: mlabonne/AlphaMonarch-7B and mlabonne/NeuralMonarch-7B.
Key Capabilities
- General Reasoning: Achieves a strong average score of 76.17 on the Open LLM Leaderboard, indicating robust performance across various benchmarks.
- Benchmark Performance:
- AI2 Reasoning Challenge (25-Shot): 73.38
- HellaSwag (10-Shot): 89.18
- MMLU (5-Shot): 64.44
- TruthfulQA (0-shot): 77.79
- Winogrande (5-shot): 84.45
- GSM8k (5-shot): 67.78
Good For
- Applications requiring solid general-purpose language understanding and generation.
- Tasks benefiting from a model with balanced performance across diverse reasoning and knowledge-based benchmarks.
- Developers looking for a 7B model with competitive scores on the Open LLM Leaderboard, as detailed here.