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  ![e2.gif](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/CbSQZghlvWbMo2EdMacXp.gif)
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- Here's the updated version:
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  # **Calcium-Opus-14B-Elite2**
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  Calcium-Opus-14B-Elite2 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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  ![e2.gif](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/CbSQZghlvWbMo2EdMacXp.gif)
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  # **Calcium-Opus-14B-Elite2**
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  Calcium-Opus-14B-Elite2 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.