Code Instruction Dataset — 17,000 Human-Reviewed Prompt & Response Pairs for LLM Fine-Tuning
This code instruction dataset is a collection of human-generated, expertly reviewed coding prompts and response pairs. This intermediate to advanced code generation training data for LLM fine-tuning includes a variety of programming languages, including Python, JavaScript, Java, C#, Swift, Go, C, C++ and TypeScript, covering tourism, finance, gaming, health and sports.
This code instruction dataset is a collection of human-generated, expertly reviewed coding prompts and response pairs. This intermediate to advanced code generation training data for LLM fine-tuning includes a variety of programming languages, including Python, JavaScript, Java, C#, Swift, Go, C, C++ and TypeScript, covering tourism, finance, gaming, health and sports.
This code instruction dataset is a collection of human-generated, expertly reviewed coding prompts and response pairs. This intermediate to advanced code generation training data for LLM fine-tuning includes a variety of programming languages, including Python, JavaScript, Java, C#, Swift, Go, C, C++ and TypeScript, covering tourism, finance, gaming, health and sports.
This code instruction dataset is a collection of human-generated, expertly reviewed coding prompts and response pairs. This intermediate to advanced code generation training data for LLM fine-tuning includes a variety of programming languages, including Python, JavaScript, Java, C#, Swift, Go, C, C++ and TypeScript, covering tourism, finance, gaming, health and sports.
Dataset specs
Type
Text
File format
xls
Amount
17K pairs
Leverage
This coding QA dataset can be used as a reference base to train models that can automatically generate new, diverse code prompts in various programming languages.
Use cases
Fine-tune LLMs to perform structured problem-solving and logical reasoning in complex coding domains with this LLM code training data.
Use this code generation training data to build and fine-tune AI moderation models that assess the accuracy, clarity and appropriateness of code prompts and programming languages.
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Dataset specs
Type
Text
File format
xls
Amount
17K pairs