jan-hq/supermario-slerp-v2
jan-hq/supermario-slerp-v2 is a 7 billion parameter language model created by Jan, utilizing the Slerp merge method to combine v1olet_marcoroni-go-bruins-merge-7B and juanako-7b-UNA. This model is a test project for exploring model merging techniques. It achieves an average score of 71.35 on the Open LLM Leaderboard, demonstrating capabilities across various reasoning and language understanding tasks within a 4096 token context window.
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Model Overview
jan-hq/supermario-slerp-v2 is a 7 billion parameter language model developed by Jan, created as a test project for model merging. It leverages the Slerp merge method to combine two distinct models: v1olet_marcoroni-go-bruins-merge-7B and juanako-7b-UNA. The base model for this merge is v1olet_marcoroni-go-bruins-merge-7B.
Key Capabilities & Performance
This model demonstrates solid performance across a range of benchmarks, as evaluated on the Open LLM Leaderboard. It achieves an average score of 71.35, with specific results including:
- AI2 Reasoning Challenge (25-Shot): 69.37
- HellaSwag (10-Shot): 86.60
- MMLU (5-Shot): 64.91
- TruthfulQA (0-Shot): 62.96
- Winogrande (5-Shot): 80.82
- GSM8k (5-Shot): 63.46
Usage and Development
This model can be run locally using Jan Desktop, an open-source, offline-first ChatGPT alternative. Jan Desktop offers a confidential environment with an open file format and OpenAI-compatible endpoints. The development of this model acknowledges contributions from mergekit, DARE, SLERP, and lm-evaluation-harness.