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- Biology Q&A multimodal dataset
- text
- images
Biology Q&A multimodal dataset
Updated May 7, 2025This curated biology multimodal dataset features over 4,000 verified question-answer pairs from curriculum-based learning. Covering fundamental to advanced topics, the dataset includes accompanying images, multiple formats of questions across four levels of complexities, and answers with explanations.
Specifications
- Modalities
- Text, Image
- Language
- English
- Volume
- 4,000+
- Average token per PRP
- 79
- Number of tokens
- 341,043
- Task category
- Questions & Answers
- Domain
- Biology
- Complexity
- 4 levels ranging from easy to very hard
Accelerate model development & training processes
Expertly-curated and verified data
We’ve curated this dataset to offer challenge-grade problems accompanied by step-by-step explanations to train and test models. The response data reflects the solution thought process to enhance model alignment with human reasoning.
Comprehensive topic coverage
Based on learning curricula with four difficulty levels and diverse question types, this dataset covers foundational to advanced topics such as photosynthesis in higher plants, respiratory systems and more.
Quality and formatting reviewed
The Q&As pass strict automated and expert-led checks for response accuracy, LaTeX formatting, solvability and language quality, ensuring consistent data reliability for your model development cycles.
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.
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Improving large language model logic and reasoning with a specialized fine-tuning dataset
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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 multimodal biology Q&A dataset
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