Model Overview

liminerity/binarized-ingotrix-slerp-7b is a 7 billion parameter language model developed by liminerity. It is a product of merging two distinct models: eren23/dpo-binarized-NeuralTrix-7B and liminerity/Ingot-7b-slerp-7-forged, utilizing a slerp (spherical linear interpolation) merge method via LazyMergekit. This merging strategy combines the strengths of its constituent models to enhance overall performance.

Key Capabilities & Performance

The model exhibits strong general-purpose language understanding and reasoning, as evidenced by its evaluation on the Open LLM Leaderboard. Key performance metrics include:

• Average Score: 76.04
• AI2 Reasoning Challenge (25-Shot): 73.21
• HellaSwag (10-Shot): 88.64
• MMLU (5-Shot): 64.85
• TruthfulQA (0-shot): 75.57
• Winogrande (5-shot): 82.87
• GSM8k (5-shot): 71.11

These scores indicate a balanced performance across various reasoning, common sense, and knowledge-based tasks.

Use Cases

This model is well-suited for applications requiring a capable 7B parameter model with solid performance across a range of benchmarks. Its balanced scores suggest suitability for tasks such as:

• General text generation and completion
• Question answering
• Reasoning tasks
• Common sense understanding