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--- |
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size_categories: n<1K |
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tags: |
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- rlfh |
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- argilla |
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- human-feedback |
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--- |
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# Dataset Card for test-argilla-dataset |
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This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets). |
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## Using this dataset with Argilla |
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To load with Argilla, you'll just need to install Argilla as `pip install argilla --pre --upgrade` and then use the following code: |
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```python |
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import argilla as rg |
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ds = rg.Dataset.from_hub("burtenshaw/test-argilla-dataset") |
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``` |
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This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation. |
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## Using this dataset with `datasets` |
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To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code: |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("burtenshaw/test-argilla-dataset") |
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``` |
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This will only load the records of the dataset, but not the Argilla settings. |
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## Dataset Structure |
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This dataset repo contains: |
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* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`. |
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* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla. |
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* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`. |
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The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**. |
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### Fields |
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The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset. |
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| Field Name | Title | Type | Required | Markdown | |
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| ---------- | ----- | ---- | -------- | -------- | |
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| text | text | text | True | False | |
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### Questions |
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The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking. |
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| Question Name | Title | Type | Required | Description | Values/Labels | |
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| ------------- | ----- | ---- | -------- | ----------- | ------------- | |
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| label | label | label_selection | True | N/A | ['positive', 'negative'] | |
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| rating | rating | rating | True | N/A | [1, 2, 3, 4, 5] | |
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| ranking | ranking | ranking | True | N/A | ['label1', 'label2', 'label3'] | |
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| comment | comment | text | True | N/A | N/A | |
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| topics | topics | multi_label_selection | True | N/A | ['topic1', 'topic2', 'topic3'] | |
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| span | span | span | True | N/A | N/A | |
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<!-- check length of metadata properties --> |
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### Metadata |
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The **metadata** is a dictionary that can be used to provide additional information about the dataset record. |
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| Metadata Name | Title | Type | Values | Visible for Annotators | |
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| ------------- | ----- | ---- | ------ | ---------------------- | |
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| comment_score | comment_score | | None - None | True | |
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### Vectors |
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The **vectors** contain a vector representation of the record that can be used in search. |
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| Vector Name | Title | Dimensions | |
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|-------------|-------|------------| |
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| vector | vector | [1, 3] | |
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### Data Instances |
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An example of a dataset instance in Argilla looks as follows: |
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```json |
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{ |
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"_server_id": "8aaf57d2-cb8e-4673-a7ce-2f684b60adf5", |
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"fields": { |
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"text": "Hello World, how are you?" |
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}, |
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"id": "4f56e32b-9582-47de-a2b1-b230732bb07b", |
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"metadata": {}, |
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"responses": { |
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"label": [ |
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{ |
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"user_id": "06f7d4c0-e048-43d2-ab3f-06f147616ac6", |
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"value": "positive" |
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} |
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] |
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}, |
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"suggestions": { |
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"label": { |
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"agent": null, |
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"score": null, |
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"value": "positive" |
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}, |
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"topics": { |
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"agent": null, |
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"score": [ |
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0.9, |
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0.8 |
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], |
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"value": [ |
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"topic1", |
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"topic2" |
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] |
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} |
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}, |
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"vectors": {} |
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} |
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``` |
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While the same record in HuggingFace `datasets` looks as follows: |
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```json |
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{ |
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"_server_id": "8aaf57d2-cb8e-4673-a7ce-2f684b60adf5", |
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"comment.suggestion": null, |
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"comment.suggestion.agent": null, |
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"comment.suggestion.score": null, |
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"comment_score": null, |
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"id": "4f56e32b-9582-47de-a2b1-b230732bb07b", |
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"label.responses": [ |
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"positive" |
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], |
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"label.responses.status": [ |
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"draft" |
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], |
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"label.responses.users": [ |
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"06f7d4c0-e048-43d2-ab3f-06f147616ac6" |
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], |
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"label.suggestion": "positive", |
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"label.suggestion.agent": null, |
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"label.suggestion.score": null, |
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"ranking.suggestion": null, |
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"ranking.suggestion.agent": null, |
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"ranking.suggestion.score": null, |
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"rating.suggestion": null, |
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"rating.suggestion.agent": null, |
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"rating.suggestion.score": null, |
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"span.suggestion": null, |
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"span.suggestion.agent": null, |
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"span.suggestion.score": null, |
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"text": "Hello World, how are you?", |
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"topics.suggestion": [ |
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"topic1", |
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"topic2" |
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], |
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"topics.suggestion.agent": null, |
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"topics.suggestion.score": [ |
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0.9, |
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0.8 |
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], |
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"vector": null |
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} |
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``` |
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### Data Splits |
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The dataset contains a single split, which is `train`. |
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## Dataset Creation |
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### Curation Rationale |
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[More Information Needed] |
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### Source Data |
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#### Initial Data Collection and Normalization |
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[More Information Needed] |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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#### Annotation guidelines |
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[More Information Needed] |
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#### Annotation process |
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[More Information Needed] |
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#### Who are the annotators? |
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[More Information Needed] |
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### Personal and Sensitive Information |
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[More Information Needed] |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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[More Information Needed] |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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[More Information Needed] |
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### Licensing Information |
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[More Information Needed] |
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### Citation Information |
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[More Information Needed] |
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### Contributions |
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[More Information Needed] |
