Text-to-Software Generation Task
A Text-to-Software Generation Task is a software generation task that accepts code generation prompts and produces source code.
- Context:
- It can be solved by an Text-to-Software Generation System (that implements text-to-software generation algorithm).
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- Example(s):
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- Counter-Example(s):
- See: Text-to-Software LLM.
References
2023
- GBard
- Prompt-based text-to-software generation is a task where a large language model (LLM) is used to generate software code from a natural language prompt. The LLM is typically trained on a large dataset of text and code, and it learns to associate natural language descriptions of code with the actual code itself.
To generate software code from a prompt, the LLM is first given the prompt. The prompt can be a simple description of the desired code, or it can be more detailed, including specific requirements for the code. The LLM then generates a piece of code that matches the prompt.
Prompt-based text-to-software generation is a relatively new task, but it has the potential to revolutionize the way software is developed. By making it possible to generate code from natural language descriptions, prompt-based text-to-software generation can make software development more accessible to people who do not have a background in programming.
- Prompt-based text-to-software generation is a task where a large language model (LLM) is used to generate software code from a natural language prompt. The LLM is typically trained on a large dataset of text and code, and it learns to associate natural language descriptions of code with the actual code itself.