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Upload folder using huggingface_hub

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  1. .argilla/dataset.json +16 -0
  2. .argilla/settings.json +54 -0
  3. .argilla/version.json +3 -0
  4. README.md +151 -31
.argilla/dataset.json ADDED
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+ {
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+ "id": "84e11a6e-17c2-4c25-ac0e-fc632ab060dc",
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+ "name": "dataset-0",
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+ "guidelines": null,
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+ "allow_extra_metadata": true,
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+ "status": "ready",
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+ "distribution": {
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+ "strategy": "overlap",
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+ "min_submitted": 1
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+ },
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+ "metadata": null,
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+ "workspace_id": "12b3405c-5832-4396-9584-926bac7e2003",
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+ "last_activity_at": "2024-12-13T14:48:42.279479",
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+ "inserted_at": "2024-12-13T14:48:42.279479",
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+ "updated_at": "2024-12-13T14:48:42.279479"
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+ }
.argilla/settings.json ADDED
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+ {
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+ "guidelines": null,
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+ "allow_extra_metadata": true,
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+ "distribution": {
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+ "strategy": "overlap",
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+ "min_submitted": 1
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+ },
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+ "fields": [
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+ {
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+ "id": "bca9353c-ac35-4392-a83d-3ceb14e5102e",
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+ "name": "text",
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+ "title": "Field Title",
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+ "required": false,
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+ "settings": {
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+ "type": "text",
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+ "use_markdown": false
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+ },
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+ "dataset_id": "84e11a6e-17c2-4c25-ac0e-fc632ab060dc",
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+ "inserted_at": "2024-12-13T14:48:42.280046",
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+ "updated_at": "2024-12-13T14:48:42.280046"
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+ }
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+ ],
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+ "questions": [],
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+ "metadata": [],
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+ "vectors": [
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+ {
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+ "id": "a2641620-b974-410c-ae29-f421171e4b78",
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+ "name": "vector-a",
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+ "title": "Vector A",
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+ "dimensions": 3,
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+ "dataset_id": "84e11a6e-17c2-4c25-ac0e-fc632ab060dc",
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+ "inserted_at": "2024-12-13T14:48:42.281170",
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+ "updated_at": "2024-12-13T14:48:42.281170"
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+ },
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+ {
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+ "id": "843fedf7-972f-4720-a1ab-050b54068322",
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+ "name": "vector-b",
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+ "title": "Vector B",
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+ "dimensions": 2,
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+ "dataset_id": "84e11a6e-17c2-4c25-ac0e-fc632ab060dc",
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+ "inserted_at": "2024-12-13T14:48:42.281488",
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+ "updated_at": "2024-12-13T14:48:42.281488"
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+ },
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+ {
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+ "id": "db18be1c-249a-491d-a079-5c188e023cd9",
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+ "name": "vector-c",
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+ "title": "Vector C",
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+ "dimensions": 4,
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+ "dataset_id": "84e11a6e-17c2-4c25-ac0e-fc632ab060dc",
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+ "inserted_at": "2024-12-13T14:48:42.281726",
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+ "updated_at": "2024-12-13T14:48:42.281726"
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+ }
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+ ]
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+ }
.argilla/version.json ADDED
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+ {
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+ "argilla": "2.6.0dev0"
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+ }
README.md CHANGED
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  ---
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- dataset_info:
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- features:
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- - name: id
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- dtype: string
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- - name: status
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- dtype: string
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- - name: inserted_at
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- dtype: timestamp[us]
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- - name: updated_at
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- dtype: timestamp[us]
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- - name: _server_id
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- dtype: string
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- - name: text
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- dtype: string
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- - name: vector.vector-a
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- sequence: float64
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- - name: vector.vector-b
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- sequence: float64
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- - name: vector.vector-c
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- dtype: 'null'
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- splits:
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- - name: train
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- num_bytes: 147
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- num_examples: 1
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- download_size: 4438
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- dataset_size: 147
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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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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+
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+ # Dataset Card for argilla-server-dataset-test-bbe69da7-49c8-4009-a9f0-48c76a8cdafc
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+
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+
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+
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+
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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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+
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+
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+ ## Using this dataset with Argilla
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+
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+ To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
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+
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+ ```python
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+ import argilla as rg
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+
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+ ds = rg.Dataset.from_hub("argilla-internal-testing/argilla-server-dataset-test-bbe69da7-49c8-4009-a9f0-48c76a8cdafc", settings="auto")
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+ ```
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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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+
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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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+
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+ ds = load_dataset("argilla-internal-testing/argilla-server-dataset-test-bbe69da7-49c8-4009-a9f0-48c76a8cdafc")
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+ ```
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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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+
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+ ## Dataset Structure
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+
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+ This dataset repo contains:
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+
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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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+
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+ The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
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+
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+ ### Fields
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+
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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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+
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+ | Field Name | Title | Type | Required |
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+ | ---------- | ----- | ---- | -------- |
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+ | text | Field Title | text | False |
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+
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+
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+ ### Questions
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+
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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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+
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+ | Question Name | Title | Type | Required | Description | Values/Labels |
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+ | ------------- | ----- | ---- | -------- | ----------- | ------------- |
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+
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+
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+ <!-- check length of metadata properties -->
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+
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+
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+
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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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+
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+ | Vector Name | Title | Dimensions |
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+ |-------------|-------|------------|
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+ | vector-a | Vector A | [1, 3] |
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+ | vector-b | Vector B | [1, 2] |
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+ | vector-c | Vector C | [1, 4] |
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+
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+
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+
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+ ### Data Splits
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+
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+ The dataset contains a single split, which is `train`.
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ [More Information Needed]
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ [More Information Needed]
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+
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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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+
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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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+
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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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+
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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]