DeepSeek-R1-Distill-Qwen-7B
About DeepSeek-R1-Distill-Qwen-7B
DeepSeek-R1-Distill-Qwen-7B is a distilled model based on Qwen2.5-Math-7B. The model was fine-tuned using 800k curated samples generated by DeepSeek-R1 and demonstrates strong reasoning capabilities. It achieved impressive results across various benchmarks, including 92.8% accuracy on MATH-500, 55.5% pass rate on AIME 2024, and a rating of 1189 on CodeForces, showing remarkable mathematical and programming abilities for a 7B-scale model
Explore how DeepSeek-R1-Distill-Qwen-7B's powerful reasoning, mathematical, and programming capabilities can be applied to solve complex, real-world problems efficiently.
Advanced Mathematical Problem Solving
Tackle intricate mathematical challenges, from theoretical physics to complex engineering, by leveraging the model's ability to generate and verify proofs, solve equations, and derive formulas.
Use Case Example:
"A materials scientist used the model to derive a novel set of partial differential equations describing a new alloy's thermal properties, significantly accelerating experimental design."
Intelligent Code Analysis & Refinement
Enhance software quality by identifying subtle bugs, optimizing algorithms, and refactoring complex code across various programming paradigms with deep logical reasoning.
Use Case Example:
"Optimized a critical data processing pipeline written in Python by identifying an inefficient sorting algorithm and suggesting a more performant, memory-efficient alternative, reducing execution time by 40%."
Quantitative Financial Modeling
Perform in-depth quantitative analysis on market data and financial reports, uncovering trends, assessing risks, and generating data-driven investment strategies.
Use Case Example:
"Developed a predictive model for cryptocurrency price movements by analyzing historical trading data and macroeconomic indicators, providing a detailed risk-adjusted portfolio recommendation."
Automated Logic & Compliance Audits
Systematically audit complex systems, from regulatory documents to network configurations, to detect logical inconsistencies, compliance gaps, and potential vulnerabilities.
Use Case Example:
"Audited a large enterprise's cloud infrastructure configuration files (Terraform/YAML) to identify security misconfigurations and policy violations, ensuring adherence to industry best practices."
Metadata
Specification
State
Deprecated
Architecture
Calibrated
No
Mixture of Experts
No
Total Parameters
7B
Activated Parameters
7B
Reasoning
No
Precision
FP8
Context length
33K
Max Tokens
16K
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