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Dataset Card for my-distiset-be899639
This dataset has been created with Argilla. As shown in the sections below, this dataset can be loaded into your Argilla server as explained in Load with Argilla, or used directly with the datasets library in Load with datasets.
Using this dataset with Argilla
To load with Argilla, you'll just need to install Argilla as pip install argilla --upgrade and then use the following code:
import argilla as rg
ds = rg.Dataset.from_hub("hemg/my-distiset-be899639", settings="auto")
This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
Using this dataset with datasets
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:
from datasets import load_dataset
ds = load_dataset("hemg/my-distiset-be899639")
This will only load the records of the dataset, but not the Argilla settings.
Dataset Structure
This dataset repo contains:
- Dataset records in a format compatible with HuggingFace
datasets. These records will be loaded automatically when usingrg.Dataset.from_huband can be loaded independently using thedatasetslibrary viaload_dataset. - The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.
- A dataset configuration folder conforming to the Argilla dataset format in
.argilla.
The dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.
Fields
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.
| Field Name | Title | Type | Required |
|---|---|---|---|
| text | Text | text | True |
Questions
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.
| Question Name | Title | Type | Required | Description | Values/Labels |
|---|---|---|---|---|---|
| labels | Labels | multi_label_selection | True | The labels of the conversation | ['positive', 'negative', 'neutral'] |
Metadata
The metadata is a dictionary that can be used to provide additional information about the dataset record.
| Metadata Name | Title | Type | Values | Visible for Annotators |
|---|---|---|---|---|
| text_length | Text Length | integer | - | True |
Vectors
The vectors contain a vector representation of the record that can be used in search.
| Vector Name | Title | Dimensions |
|---|---|---|
| text_embeddings | text_embeddings | [1, 256] |
Data Splits
The dataset contains a single split, which is train.
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation guidelines
Please review the text and provide or correct the label where needed.
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
[More Information Needed]
Contributions
[More Information Needed]
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