Qwen 2.5 Coder is better!
So essentially,
Qwen2.5 Coder exceeds in all coding benchmarks!
Paper: Qwen2.5-Coder Technical Report (23 Pages)
Github: https://github.com/QwenLM/Qwen2.5-Coder
Researchers from Qwen and Alibaba are interested in better coding LLMs.
Hmm..What’s the background?
Qwen2.5-Coder represents an upgrade from its predecessor, CodeQwen1.5, designed for superior performance in coding tasks across different model sizes. The authors emphasize a data-centrist approach to LLM training, acknowledging the significant impact of large-scale, high-quality, and diverse datasets on model performance.
Ok, So what is proposed in the research paper?
Qwen2.5-Coder's training data consists of various types - source code, text-code grounding, synthetic, math, and general text data. The authors meticulously experimented with different data ratios to find an optimal balance for robust performance across coding, mathematics, and general language tasks
To ensure the generation of high-quality code, the authors incorporated an executor to validate the generated synthetic data, retaining only the executable code.
Qwen2.5-Coder is trained in three stages: file-level pretraining, repo-level pretraining, and instruction tuning. This approach helps the model achieve proficiency in handling different coding scenarios, from understanding individual files to navigating complex code repositories.
What’s next?
Underscoring their commitment to fostering research, the Qwen2.5-Coder models are open-sourced, encouraging community engagement and promoting broader adoption in practical applications. Future research aims to explore the impact of scaling up data and model sizes and enhancing the reasoning capabilities of these code LLMs.
So essentially,
Qwen2.5 Coder exceeds in all coding benchmarks!
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