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Alpaca Instruction NLU Dataset
Data Science and Analytics
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Free
About
This dataset, titled "TokenBender: 122k Alpaca-Style Instructions Word-Level Classification Towards Accurate Natural Language Understanding", offers a collection of 122,000 Alpaca-style instructions, each paired with corresponding input, text, and output for word-level classification. It is designed to facilitate natural language understanding (NLU) research by providing entries from diverse areas such as programming code instructions and gaming instructions, presented at varying levels of complexity. The dataset assists developers aiming to apply natural language processing (NLP) techniques, offering insights into how to improve the accuracy and ease the comprehension of human language commands. Utilising this dataset, one can develop advanced algorithms, such as neural networks or decision trees, capable of quickly understanding commands in various languages and bridging the gap between machines and humans for practical applications. It serves as a valuable resource for those seeking to gain insight into NLU through data science approaches.
Columns
- input: The input associated with the instruction.
- text: The Alpaca-Style instruction that corresponds to the user's input.
- output: The associated output for word-level classification.
Distribution
The dataset is structured as a
train.csv file, containing 122,000 Alpaca-Style Instructions. The input column holds 121,683 unique values, the text column contains 121,957 unique values, and the output column features 120,724 unique values.Usage
This dataset is ideal for:
- Developing AI-based algorithms to accurately understand the meaning of natural language instructions.
- Training and testing machine learning models for classifying specific words and phrases within natural language instructions.
- Training deep learning models to generate visual components based on given input, text, and output values.
- Applying and enhancing natural language processing techniques for machine comprehension.
- Developing advanced neural networks or decision trees for understanding commands across languages.
Coverage
The dataset's coverage is global. It was listed on 16/06/2025. It includes diverse instruction types, such as programming code and gaming instructions. No specific historical time range or demographic scope is detailed beyond the listing date.
License
CC0
Who Can Use It
- Developers focused on applying and improving natural language processing techniques.
- Researchers engaged in natural language understanding.
- Data scientists seeking insights into NLU through data science methods.
- Anyone developing AI-based algorithms for natural language comprehension.
- Teams and individuals training machine learning or deep learning models for classification or generation tasks related to natural language.
Dataset Name Suggestions
- Alpaca Instruction NLU Dataset
- TokenBender Word Classification Data
- Natural Language Understanding Instructions
- Alpaca-Style NLP Training Set
- Word-Level Text Classification Data
Attributes
Original Data Source: Alpaca
QUALITY