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# **COCO-7B-Instruct**
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COCO-7B-Instruct is based on a 7B-parameter architecture, optimized for instruction-following tasks and advanced reasoning capabilities. Fine-tuned on a diverse set of datasets and leveraging chain-of-thought (CoT) reasoning, it excels in understanding contexts, solving mathematical problems, and generating detailed, structured responses. Its lightweight architecture ensures efficiency while maintaining performance, making it suitable for applications requiring logical reasoning, concise explanations, and multi-step problem-solving.
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Key improvements include:
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1. **Enhanced Instruction Following**: This model is designed to precisely follow complex instructions and generate coherent, concise outputs, even for nuanced or multi-layered prompts.
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# **COCO-7B-Instruct [chain of continuesness]**
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COCO-7B-Instruct `[ chain of continuesness ]` is based on a 7B-parameter architecture, optimized for instruction-following tasks and advanced reasoning capabilities. Fine-tuned on a diverse set of datasets and leveraging chain-of-thought (CoT) reasoning, it excels in understanding contexts, solving mathematical problems, and generating detailed, structured responses. Its lightweight architecture ensures efficiency while maintaining performance, making it suitable for applications requiring logical reasoning, concise explanations, and multi-step problem-solving.
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Key improvements include:
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1. **Enhanced Instruction Following**: This model is designed to precisely follow complex instructions and generate coherent, concise outputs, even for nuanced or multi-layered prompts.
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