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Deepseek R1 Distill Qwen 7B
Overview :
DeepSeek-R1-Distill-Qwen-7B is a reinforcement learning-optimized reasoning model distilled from Qwen-7B. It excels in mathematical, coding, and reasoning tasks, generating high-quality reasoning chains and solutions. This model significantly enhances reasoning capabilities and efficiency through large-scale reinforcement learning and data distillation techniques, making it suitable for scenarios requiring complex reasoning and logical analysis.
Target Users :
This model is suitable for developers, researchers, and educators who require efficient reasoning and logical analysis. It helps users quickly address complex mathematical and programming problems, thereby enhancing productivity.
Use Cases
Assist participants in math competitions by quickly generating problem-solving ideas.
Provide programming professionals with optimization suggestions to improve code quality.
Aid educators by generating teaching cases and problem-solving steps.
Features
Supports mathematical reasoning and can solve complex mathematical problems.
Provides code generation and optimization capabilities for programming assistance.
Generates high-quality reasoning chains to support step-by-step answers to complex issues.
Optimizes model performance through reinforcement learning, improving reasoning accuracy.
Open-source model that supports community use and further development.
How to Use
1. Visit the Hugging Face official page and download the model weights.
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2. Load the model using a supported framework, such as Transformers.
3. Adjust model parameters according to your needs, such as temperature and maximum generation length.
4. Input your question or task, and the model will generate reasoning results.
5. Evaluate and optimize the generated results to meet your practical requirements.
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