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Model: DQN-Labs-Community/dqnMath-v1-GGUF
Source: Original Platform

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DQN-Math-v1.Q4_K_M.gguf

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DQN-Math-v1.f16.gguf

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README.md

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

dqnMath.png

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