The University of Illinois at Urbana-Champaign (UIUC) and Tsinghua University jointly launched an impressive new large-scale language model-Magicoder. This model uses only 7 billion parameters, but shows excellent performance comparable to top models in the field of code generation. This is undoubtedly a major breakthrough in the field of artificial intelligence. What’s even more surprising is that its code, weights and data have been fully open source, providing valuable resources to developers around the world. Magicoder's success is due to its unique OSS-INSTRUCT method, which can generate diverse, real and controllable encoded instruction data, highlighting the important role of data authenticity in instruction fine-tuning. Its excellent performance on Python and other programming languages and data science libraries, especially its 8.3 percentage point performance improvement on the DS-1000 data set, fully proves the powerful capabilities of Magicoder.
Magicoder uses the OSS-INSTRUCT method to generate diverse, real and controllable encoded instruction data, emphasizing the importance of authenticity for instruction adjustment. In performance evaluations in the fields of Python, other programming languages, and data science libraries, Magicoder performed well, especially on the DS-1000 dataset, improving by 8.3 percentage points. The release of Magicoder marks an important step in the field of code generation.
Magicoder's open source not only lowers the entry threshold for code generation technology, but also provides a solid foundation for future research and innovation. It is believed that in the near future, Magicoder will have a profound impact on the field of code generation and promote the further development of artificial intelligence technology.