Cogito 70B - Details

Cogito 70B is a large language model developed by Deep Cogito, a company specializing in advanced AI research. With 70b parameters, it is designed to excel in hybrid reasoning and self-reflection, enhancing its problem-solving capabilities. The model is released under the Apache License 2.0, allowing for flexible use and modification in both academic and commercial settings.

Cogito v1 preview is an instruction-tuned generative model optimized for coding, STEM, instruction following, and general helpfulness. It leverages Iterated Distillation and Amplification (IDA) for alignment, enabling robust and safe interactions. The model supports hybrid reasoning with both standard and self-reflective modes, enhancing its ability to tackle complex tasks. Trained in over 30 languages with a context length of 128k, it offers broad linguistic flexibility. Additionally, it enables tool calling in both standard and extended thinking modes, expanding its utility for real-world applications.

Cogito 70B is a large language model with 70b parameters, placing it in the very large models category, which enables it to handle complex tasks but requires significant computational resources. It also features a 128k context length, making it suitable for processing very long texts, though this demands substantial memory and processing power.

• Parameter Size: 70b
• Context Length: 128k

Cogito 70B is a versatile large language model designed for coding, STEM problem solving, instruction following, and tool calling, with potential applications in areas that require complex reasoning and adaptability. Its 70b parameter size and 128k context length suggest it could support possible uses such as generating code snippets, assisting with scientific calculations, interpreting detailed instructions, or integrating with external tools to enhance task execution. However, these possible uses would need thorough exploration to ensure alignment with specific requirements and constraints. The model’s hybrid reasoning capabilities might also enable possible applications in scenarios requiring iterative problem-solving or dynamic decision-making, though further testing would be necessary.

• coding
• stem problem solving
• instruction following
• tool calling

Cogito 70B is a large-scale language model with 70b parameters and a 128k context length, making it a possible tool for tasks requiring advanced reasoning and adaptability. Its possible applications could include assisting with complex coding challenges, where its hybrid reasoning might help generate or debug code. It could also serve as a possible aid for STEM problem-solving, leveraging its extensive training to tackle multi-step scientific or mathematical tasks. Possible uses might extend to instruction-following scenarios, where its ability to parse detailed directives could enhance task execution. Additionally, it could act as a possible platform for tool calling, integrating external resources to improve efficiency in dynamic workflows. These possible applications would require careful evaluation to ensure alignment with specific needs and constraints.

• coding
• STEM problem solving
• instruction following
• tool calling

Cogito 70B in its medium q4 version requires hardware capable of handling large-scale models with optimized precision, likely needing a GPU with at least 24GB VRAM for efficient operation, though multiple GPUs may be necessary for full performance. This possible configuration balances computational efficiency and accuracy, making it suitable for users with mid-to-high-end graphics cards. The q4 version reduces memory demands compared to fp16 or q8, but the model’s 70b parameters still necessitate careful hardware planning.

• fp16
• q4
• q8

Cogito 70B is a large language model with 70b parameters and a 128k context length, designed for hybrid reasoning and self-reflection to improve problem-solving. It is developed by Deep Cogito and released under the Apache License 2.0, offering flexibility for diverse applications.

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