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  Calcium-Opus-14B-Elite3 is based on the Qwen 2.5 14B modality architecture, designed to enhance the reasoning capabilities of 14B-parameter models. These models have proven effective in context understanding, reasoning, and mathematical problem-solving. It has been fine-tuned using a long chain-of-thought reasoning model and specialized datasets, with a focus on chain-of-thought (CoT) reasoning for problem-solving. This model is optimized for tasks requiring logical reasoning, detailed explanations, and multi-step problem-solving, making it ideal for applications such as instruction-following, text generation, and complex reasoning tasks.
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- # **Open-Evals**
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- | Rank | Model | Average | IFEval | BBH | MATH | GPQA | MUSR | MMLU | CO₂ Consumption | Dated |
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- | ---- | ----------------------------------------------------------------------------------------------------- | ------- | ------ | ----- | ----- | ----- | ----- | ----- | --------------- | ---------- |
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- | 108 | [prithivMLmods/Calcium-Opus-14B-Elite3](https://huggingface.co/prithivMLmods/Calcium-Opus-14B-Elite3) | 38.38 | 60.52 | 46.93 | 37.69 | 16.55 | 20.78 | 47.80 | 2.01 | 01/23/2025 |
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  Key improvements include:
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  1. **Enhanced Knowledge and Expertise**: The model demonstrates significantly more knowledge and greatly improved capabilities in coding and mathematics, thanks to specialized expert models in these domains.
 
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  Calcium-Opus-14B-Elite3 is based on the Qwen 2.5 14B modality architecture, designed to enhance the reasoning capabilities of 14B-parameter models. These models have proven effective in context understanding, reasoning, and mathematical problem-solving. It has been fine-tuned using a long chain-of-thought reasoning model and specialized datasets, with a focus on chain-of-thought (CoT) reasoning for problem-solving. This model is optimized for tasks requiring logical reasoning, detailed explanations, and multi-step problem-solving, making it ideal for applications such as instruction-following, text generation, and complex reasoning tasks.
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  Key improvements include:
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  1. **Enhanced Knowledge and Expertise**: The model demonstrates significantly more knowledge and greatly improved capabilities in coding and mathematics, thanks to specialized expert models in these domains.