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.argilla/dataset.json

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+{
+  "id": "8131d925-aa6e-4ceb-ad9b-cb54d6a8dab9",
+  "name": "nairadataset123456",
+  "guidelines": null,
+  "allow_extra_metadata": true,
+  "status": "ready",
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "metadata": {
+    "repoId": "Faiqa01/datastet1",
+    "subset": "default",
+    "split": "train",
+    "mapping": {
+      "fields": [
+        {
+          "source": "review",
+          "target": "review"
+        }
+      ],
+      "metadata": [
+        {
+          "source": "id",
+          "target": "id"
+        }
+      ],
+      "suggestions": []
+    },
+    "imported": "UI"
+  },
+  "workspace_id": "80d804db-5ec5-40ff-9373-b1c53b9af290",
+  "last_activity_at": "2025-10-04T16:42:27.963090",
+  "inserted_at": "2025-10-04T16:37:51.177292",
+  "updated_at": "2025-10-04T16:37:52.238169"
+}

.argilla/settings.json

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+{
+  "guidelines": null,
+  "allow_extra_metadata": true,
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "fields": [
+    {
+      "id": "586532c5-5053-4239-a091-140050f1edbc",
+      "name": "review",
+      "title": "review",
+      "required": false,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "8131d925-aa6e-4ceb-ad9b-cb54d6a8dab9",
+      "inserted_at": "2025-10-04T16:37:51.468542",
+      "updated_at": "2025-10-04T16:37:51.468542"
+    }
+  ],
+  "questions": [
+    {
+      "id": "f989bc13-7a2f-4a76-8f2b-257c37a86c58",
+      "name": "label_0",
+      "title": "label_0",
+      "description": null,
+      "required": true,
+      "settings": {
+        "type": "label_selection",
+        "options": [
+          {
+            "value": "positive",
+            "text": "positive",
+            "description": null
+          },
+          {
+            "value": "negative",
+            "text": "negative",
+            "description": null
+          },
+          {
+            "value": "neutral",
+            "text": "neutral",
+            "description": null
+          }
+        ],
+        "visible_options": null
+      },
+      "dataset_id": "8131d925-aa6e-4ceb-ad9b-cb54d6a8dab9",
+      "inserted_at": "2025-10-04T16:37:51.716584",
+      "updated_at": "2025-10-04T16:37:51.716584"
+    }
+  ],
+  "metadata": [
+    {
+      "id": "a999b0f4-4c3b-4bda-8d28-12bcf52d9eaf",
+      "name": "id",
+      "title": "id",
+      "settings": {
+        "type": "integer",
+        "min": null,
+        "max": null
+      },
+      "visible_for_annotators": true,
+      "dataset_id": "8131d925-aa6e-4ceb-ad9b-cb54d6a8dab9",
+      "inserted_at": "2025-10-04T16:37:51.972484",
+      "updated_at": "2025-10-04T16:37:51.972484"
+    }
+  ],
+  "vectors": []
+}

.argilla/version.json

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+{
+  "argilla": "2.8.0"
+}

README.md

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 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: status
-    dtype: string
-  - name: inserted_at
-    dtype: timestamp[us]
-  - name: updated_at
-    dtype: timestamp[us]
-  - name: _server_id
-    dtype: string
-  - name: review
-    dtype: string
-  - name: label_0.responses
-    sequence: string
-  - name: label_0.responses.users
-    sequence: string
-  - name: label_0.responses.status
-    sequence: string
-  - name: metadata.id
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 158310
-    num_examples: 100
-  download_size: 111183
-  dataset_size: 158310
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+
+# Dataset Card for nairadataset123456
+
+
+
+
+
+
+
+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).
+
+
+## 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:
+
+```python
+import argilla as rg
+
+ds = rg.Dataset.from_hub("Faiqa01/nairadataset123456", 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:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("Faiqa01/nairadataset123456")
+```
+
+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 using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`.
+* The [annotation guidelines](#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 |
+| ---------- | ----- | ---- | -------- |
+| review | review | text | False |
+
+
+### 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 |
+| ------------- | ----- | ---- | -------- | ----------- | ------------- |
+| label_0 | label_0 | label_selection | True | N/A | ['positive', 'negative', 'neutral'] |
+
+
+<!-- check length of metadata properties -->
+
+### 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 |
+| ------------- | ----- | ---- | ------ | ---------------------- |
+ | id | id | integer |  -  | True |
+
+
+
+
+
+### 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
+
+[More Information 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]