---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: premise
    dtype: string
  - name: hypothesis
    dtype: string
  - name: answer
    dtype: string
  - name: dataset
    dtype: string
  - name: translated
    dtype: bool
  - name: input
    dtype: string
  - name: output
    dtype: string
  - name: conversations
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
  splits:
  - name: train
    num_bytes: 864378584
    num_examples: 923646
  - name: validation
    num_bytes: 25124637
    num_examples: 23541
  - name: test
    num_bytes: 23873116
    num_examples: 23023
  download_size: 285523301
  dataset_size: 913376337
configs:
- config_name: en
  data_files:
  - split: train
    path: en/train-*
  - split: validation
    path: en/validation-*
  - split: test
    path: en/test-*
- config_name: cs
  data_files:
  - split: train
    path: cs/train-*
  - split: validation
    path: cs/validation-*
  - split: test
    path: cs/test-*
license: cc-by-nc-sa-4.0
task_categories:
- text-generation
- text-classification
language:
- cs
- en
tags:
- NLI
size_categories:
- 1M<n<10M
source_datasets:
- ctu-aic/enfever_nli
- facebook/anli
- stanfordnlp/snli
- chenxwh/AVeriTeC
- ctu-aic/anli_cs
- ctu-aic/snli_cs
- ctu-aic/csfever_nli
- ctu-aic/ctkfacts_nli
multilinguality:
- multilingual
---

# Dataset Card for Natural Language Inference Instruction Tuning Collection

<!-- Provide a quick summary of the dataset. -->
This dataset is a collection of various NLI datasets in Czech and English, transformed into an instruction tuning format based on the FLAN approach.

## Dataset Details

### Dataset Description

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- **Curated by:** Artificial Intelligence Center, FEE, CTU in Prague
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- **Language(s) (NLP):** Czech (cs, ces), English (en)
- **License:** [cc-by-nc-sa-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed)

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## Uses

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### Direct Use

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### Out-of-Scope Use

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## Dataset Structure

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## Dataset Creation

### Curation Rationale

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### Source Data

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#### Data Collection and Processing

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#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

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## Bias, Risks, and Limitations

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### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [TBD]

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## Glossary [optional] -->

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