gagan3012/MetaModelv3
gagan3012/MetaModelv3 is a 10.7 billion parameter language model, a hybrid of jeonsworld/CarbonVillain-en-10.7B-v4 and jeonsworld/CarbonVillain-en-10.7B-v2, with a 4096 token context length. It demonstrates strong general reasoning capabilities, achieving an average score of 74.39 on the Open LLM Leaderboard, making it suitable for a range of general-purpose language understanding and generation tasks.
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MetaModelv3 Overview
MetaModelv3 is a 10.7 billion parameter language model, built as a hybrid of two CarbonVillain-en-10.7B variants: jeonsworld/CarbonVillain-en-10.7B-v4 and jeonsworld/CarbonVillain-en-10.7B-v2. This model features a context length of 4096 tokens.
Performance Highlights
Evaluated on the Open LLM Leaderboard, MetaModelv3 achieved an average score of 74.39. Key benchmark results include:
- ARC (25-shot): 71.16
- HellaSwag (10-shot): 88.39
- MMLU (5-shot): 66.32
- TruthfulQA (0-shot): 71.86
- Winogrande (5-shot): 83.35
- GSM8K (5-shot): 65.28
These scores indicate solid performance across various reasoning, common sense, and knowledge-based tasks, including mathematical problem-solving (GSM8K).
Use Cases
MetaModelv3 is well-suited for applications requiring:
- General-purpose text generation and understanding.
- Reasoning tasks, as evidenced by its ARC and MMLU scores.
- Common sense reasoning, supported by HellaSwag and Winogrande results.
- Fact-based question answering, indicated by its TruthfulQA performance.