Complete-it

Dataset Summary

The Complete-it dataset is designed for training and evaluating text auto-completion models. It provides structured prompt–completion pairs that can be used to fine-tune language models for predictive typing, code completion, or general text continuation tasks.

This dataset is intended for researchers, developers, and practitioners who want to explore completion-based modeling in natural language processing.

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Supported Tasks and Benchmarks

• Text Auto-Completion: Predicting the next sequence of tokens given a partial input.
• Language Modeling: Training models to generate coherent continuations of text.
• Instruction Tuning (optional): Can be adapted for instruction–response style fine-tuning if reformatted.

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Languages

• The dataset is primarily in English.
• It can be extended or adapted for multilingual completion tasks.

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Dataset Structure

• Input: A partial text sequence (prompt).
• Output: The expected continuation (completion).

Example:

{
  "prompt": "The quick brown fox",
  "completion": " jumps over the lazy dog."
}

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Data Splits

• train: Main split for model training.
• validation: For hyperparameter tuning and evaluation.
• test: For final benchmarking.

(Adjust based on your actual splits — if you only have one file, note that here.)

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Usage

You can load the dataset directly with the Hugging Face datasets library:

from datasets import load_dataset

dataset = load_dataset("Parveshiiii/Complete-it")

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Intended Use

• Research on auto-completion and predictive text.
• Fine-tuning small to medium language models for lightweight completion tasks.
• Educational purposes in demonstrating dataset formatting for completion models.

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Limitations

• The dataset may not cover all domains or writing styles.
• Quality of completions depends on the diversity of the source material.
• Not intended for safety-critical applications without further filtering and evaluation.

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Citation

If you use this dataset, please cite it as:

@dataset{Parveshiiii_Complete-it,
  title     = {Complete-it},
  author    = {Parvesh Rawal},
  year      = {2025},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/Parveshiiii/Complete-it}
}

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