初始化项目，由ModelHub XC社区提供模型

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

README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- science
+- reasoning
+- advanced-reasoning
+- thinking
+- small-model
+- efficient
+- education
+- local
+- qwen
+- qwen3
+- qwen3.5
+- 4b
+- small
+- cot
+- chainofthought
+- deep-thinking
+- physics
+- chemistry
+- biology
+- logic
+- daily-use
+- localai
+- ai
+- gpt
+- dqnlabs
+- dqngpt
+- gguf
+- lmstudio
+- ollama
+pipeline_tag: text-generation
+---
+
+# dqnScience-v1
+
+dqnScience-v1 is a 4B-parameter flagship reasoning model designed for deep thinking, scientific problem solving, and complex multi-step reasoning.
+
+Unlike lightweight fast-response models, dqnScience-v1 is built to **think longer, reason deeper, and solve harder problems**—often performing far above its size class.
+
+![dqnScience Banner](dqnScience.png)
+
+---
+
+## Model Description
+
+- **Model type:** Causal Language Model  
+- **Parameters:** 4B  
+- **Primary use:** Scientific reasoning and advanced problem solving  
+- **Style:** Deep, structured, step-by-step reasoning  
+
+dqnScience-v1 prioritizes **reasoning quality over speed**, making it ideal for problems that require careful thought, abstraction, and layered logic.
+
+---
+
+## Intended Uses
+
+### Direct Use
+
+- Solving physics, chemistry, and biology problems  
+- Logical and analytical reasoning tasks  
+- Multi-step problem solving  
+- Conceptual understanding of scientific topics  
+- Competitive exam-style questions (college level to moderate)  
+
+---
+
+## Key Characteristics
+
+- Strong multi-step reasoning ability  
+- Produces structured and detailed explanations  
+- Excels at breaking down complex problems  
+- Performs above typical 4B models in reasoning capability  
+- Designed for consistency and logical correctness  
+- Handles abstract and conceptual questions effectively  
+
+---
+
+## Usage
+
+dqnScience-v1 is available in multiple formats:
+
+- **GGUF** → llama.cpp, LM Studio  
+- **MLX** → optimized for Apple Silicon  (coming soon)
+- **HF Transformers** → universal compatibility  
+
+---
+
+## Training Details
+
+dqnScience-v1 is fine-tuned with a strong focus on reasoning-heavy datasets, emphasizing:
+
+- Deep chain-of-thought reasoning  
+- Scientific and logical problem solving  
+- Conceptual clarity over memorization  
+- Robust multi-step inference  
+
+---
+
+## Limitations
+
+- Slower than lightweight models due to deeper reasoning  
+- May over-explain simple questions 
+- Not optimized for casual or short-form responses  
+- Performance may vary on highly specialized or research-level topics  
+
+---
+
+## Efficiency
+
+Despite its strong reasoning capabilities, dqnScience-v1 is optimized to run moderately efficiently on consumer hardware, with support for quantized formats.
+
+---
+
+## License
+
+Apache 2.0
+
+---
+
+## Author
+
+Developed by DQN Labs.
+
+Special thanks to Ram2 for quantization.
+
+This model card was generated with the help of dqnGPT v1.