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Datasets:
SOULAMA
/
QA-text-generation-alpaca-data-cleaned

Tasks:
Text Generation
Question Answering
Formats:
parquet
Languages:
English
Size:
10K - 100K
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
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1
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input_ids
listlengths
4
6.24k
attention_mask
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6.24k
labels
listlengths
2
6.26k
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Dataset Card for mBART-QA-Processed

This dataset consists of tokenized pairs of instructions and contexts designed for fine-tuning Sequence-to-Sequence models (like mBART or T5) on Question Answering tasks.

Dataset Details

Dataset Description

The dataset is a processed version of a Question Answering corpus (SQuAD-like). It has been formatted to follow a specific prompt structure: instruction: {question} input: {context}. The targets (labels) are the direct text answers.

  • Curated by: SOULAMA H.Ismael
  • Language(s) (NLP): English (en)
  • License: Apache-2.0

Dataset Sources

Uses

Direct Use

This dataset is intended for fine-tuning generative models to perform document-based question answering. It is optimized for text2text-generation tasks where the model must generate a concise answer based on a provided snippet.

Out-of-Scope Use

The dataset should not be used for open-domain QA without providing a context, as it is designed for grounded generation. It is not suitable for training models in languages other than English without further augmentation.

Dataset Structure

The dataset contains three main features:

  • input_ids: Token
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