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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ tags:
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+ - math
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+ - reasoning
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+ - small-model
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+ - efficient
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+ - education
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+ - local
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+ - qwen
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+ - qwen3
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+ - qwen3.5
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+ - 4b
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+ - small
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+ - mathematics
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+ - cot
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+ - chainofthought
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+ - thinking
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+ - daily-use
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+ - localai
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+ - ai
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+ - gpt
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+ - dqnlabs
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+ - dqngpt
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+ - gguf
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+ - lmstudio
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+ - ollama
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # dqnMath-v1
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+
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+ dqnMath-v1 is a 4B-parameter language model designed for fast, clear, and reliable mathematical problem solving.
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+
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+ It focuses on solving problems efficiently, with concise steps and minimal unnecessary explanation. It's optimized for solving daily mathematical problems quickly and efficiently, with minimal token count.
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+
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+ ![dqnCode Banner](dqnMath.png)
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+ ---
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+
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+ ## Model Description
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+
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+ - **Model type:** Causal Language Model
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+ - **Parameters:** 4B
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+ - **Primary use:** Mathematical problem solving
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+ - **Style:** Direct answers with optional, minimal step-by-step reasoning
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+
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+ dqnMath v1 4B is optimized for clarity and speed rather than long-form reasoning or benchmark performance.
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+
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+ ---
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+
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+ ## Intended Uses
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+
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+ ### Direct Use
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+
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+ - Solving school-level math problems
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+ - Performing quick calculations
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+ - Explaining basic mathematical steps
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+ - Assisting with homework and practice
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+ - Low to moderate reasoning-heavy math
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+
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+ ---
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+
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+ ## Key Characteristics
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+
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+ - Produces concise and readable solutions
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+ - Prioritizes correctness over verbosity
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+ - Uses structured reasoning when needed
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+ - Designed for consistent outputs across similar problems
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+ - Reliable and minimal hallucination
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+
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+ ---
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+
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+ ## Example
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+
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+ **Input**
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+ ```text
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+ Solve: 2x + 3 = 7
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+ ```
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+
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+ **Output**
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+ ```text
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+ 2x = 4
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+ x = 2
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+ ```
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+
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+ ---
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+
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+ **Input**
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+ ```text
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+ Convert 0.333... to a fraction
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+ ```
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+
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+ **Output**
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+ ```text
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+ Let x = 0.333...
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+
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+ 10x = 3.333...
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+ 10x - x = 3
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+ 9x = 3
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+ x = 1/3
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+ ```
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+
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+ ---
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+
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+ ## Usage
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+
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+ This model is available on many platforms and is compatible with many formats!
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+
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+ The GGUF format is compatible with llama.cpp and LM Studio.
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+ Other formats include MLX (LM Studio, optimized for Apple devices), and HF (universal compatibility).
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+
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+
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+ ---
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+
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+ ## Training Details
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+
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+ dqnMath-v1 is fine-tuned for structured mathematical reasoning and concise problem-solving.
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+
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+ The training process emphasizes:
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+
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+ - Step-by-step clarity
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+ - Reduced verbosity
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+ - Reliable first-attempt answers
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+
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+ ---
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+
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+ ## Limitations
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+
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+ - Limited performance on advanced mathematics
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+ - Not optimized for non-mathematical domains
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+ - May simplify explanations rather than explore deeply
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+
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+ ---
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+
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+ ## Efficiency
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+
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+ dqnMath-v1 is designed to run efficiently on consumer hardware, with support for quantized formats.
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+
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+ ---
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+
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+ ## License
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+
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+ Apache 2.0
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+
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+ ---
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+
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+ ## Author
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+
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+ Developed by DQN Labs.
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+ This model card was generated with the help of dqnGPT v0.2!