- Data & AI Solutions
- Off-the-Shelf Datasets
- Coding prompt-response pairs dataset
- text
Coding prompt-response pairs dataset
Updated May 7, 2025This dataset of more than 1,700 expert-curated prompt-response pairs (PRPs) is designed to enhance code comprehension and generation capabilities in AI models. Spanning a wide range of programming languages, it presents a diverse mix of syntax and paradigms to ensure broad applicability across various coding styles and environments.
Specifications
- Modalities
- Text
- Language
- English
- Volume
- 1700+
- Average token per PRP
- 634
- Number of tokens
- 1,135,567
- Task category
- Prompt-response pairs
- Domain
- Coding
- Complexity
- 3 levels ranging from moderate to very hard
Accelerate model development & training processes
High‑quality code and explanations
Each entry includes both working code snippets and clear, concise explanations. This dual structure empowers models to not only generate correct code but also articulate the reasoning behind each solution, improving interpretability and trustworthiness.
Comprehensive topic coverage
Curated by software engineering experts, the Q&A pairs reflect authentic developer challenges such as code completion, code review, comment generation, debugging tasks, troubleshooting, CLI, testing and more.
Confidently train and evaluate models
Leverage standardized problem sets and ground‑truth answers to improve and evaluate your model’s programming accuracy, efficiency and generalization.
Explore our success stories
Evaluating a conversational AI model with a highly complex multimodal STEM dataset
Discover how our off-the-shelf science, technology, engineering and mathematics (STEM) dataset contributed to enhancing scientific reasoning and visual processing capabilities in a chatbot model crafted by a leading-edge tech and AI company.
4485Physics prompt-response pairs
9606Math prompt-response pairs
Improving large language model logic and reasoning with a specialized fine-tuning dataset
Explore how TELUS Digital created an off-the-shelf dataset to advance the capabilities of large language models (LLMs).
50KSTEM-based prompt-response pairs created
300Highly-skilled contributors
Evaluating a conversational AI model with a highly complex multimodal STEM dataset
Discover how our off-the-shelf science, technology, engineering and mathematics (STEM) dataset contributed to enhancing scientific reasoning and visual processing capabilities in a chatbot model crafted by a leading-edge tech and AI company.
4485Physics prompt-response pairs
9606Math prompt-response pairs
Improving large language model logic and reasoning with a specialized fine-tuning dataset
Explore how TELUS Digital created an off-the-shelf dataset to advance the capabilities of large language models (LLMs).
50KSTEM-based prompt-response pairs created
300Highly-skilled contributors
Access the coding prompt-response pairs dataset
Connect with our experts for pricing and samples.
Explore our custom AI solutions
