CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
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Abstract
Program synthesis strives to generate a computer program as a solution to a given problem specification, expressed with input-output examples or natural language descriptions. The prevalence of large language models advances the state-of-the-art for program synthesis, though limited training resources and data impede open access to such models. To democratize this, we train and release a family of large language models up to 16.1B parameters, called CODEGEN, on natural language and programming language data, and open source the training library JAXFORMER. We show the utility of the trained model by demonstrating that it is competitive with the previous state-of-the-art on zero-shot Python code generation on…
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Keywords
- Computer science
- Python (programming language)
- Programming language
- Source code
- Benchmark (surveying)
- Program synthesis
- Language model
- Open source
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