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.argilla/dataset.json

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+{"id": "3548ba81-5e1b-4dff-be28-17a6cf37c531", "inserted_at": "2025-07-30T07:23:18.310500", "updated_at": "2025-07-30T07:23:18.700358", "name": "ag_news", "status": "ready", "guidelines": null, "allow_extra_metadata": false, "distribution": {"strategy": "overlap", "min_submitted": 1}, "workspace_id": "cd735cee-80a1-471e-a871-36d80c808159", "last_activity_at": "2025-07-30T07:43:40.689964"}

.argilla/settings.json

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+{"guidelines": null, "questions": [{"id": "fb7eb807-eeb3-4f9b-8708-eebc1a8cdbe9", "inserted_at": "2025-07-30T07:23:18.559685", "updated_at": "2025-07-30T07:23:18.559685", "name": "label", "settings": {"type": "label_selection", "options": [{"value": "Business", "text": "Business", "description": null}, {"value": "Sci/Tech", "text": "Sci/Tech", "description": null}, {"value": "Sports", "text": "Sports", "description": null}, {"value": "World", "text": "World", "description": null}], "visible_options": 4}, "title": "Classify the text:", "description": null, "required": true, "dataset_id": "3548ba81-5e1b-4dff-be28-17a6cf37c531", "type": "label_selection"}, {"id": "21de89eb-1d74-49d4-83a7-7f7aeb2ca8f3", "inserted_at": "2025-07-30T07:23:18.624962", "updated_at": "2025-07-30T07:23:18.624962", "name": "entities", "settings": {"type": "span", "allow_overlapping": false, "field": "text", "options": [{"value": "PERSON", "text": "PERSON", "description": null}, {"value": "ORG", "text": "ORG", "description": null}, {"value": "LOC", "text": "LOC", "description": null}, {"value": "EVENT", "text": "EVENT", "description": null}], "visible_options": 4}, "title": "Highlight all the entities in the text:", "description": null, "required": true, "dataset_id": "3548ba81-5e1b-4dff-be28-17a6cf37c531", "type": "span"}], "fields": [{"id": "821c3d57-7580-447d-8a99-ebe1b6a5faeb", "inserted_at": "2025-07-30T07:23:18.481633", "updated_at": "2025-07-30T07:23:18.481633", "name": "text", "settings": {"type": "text", "use_markdown": false}, "title": "text", "required": true, "description": null, "dataset_id": "3548ba81-5e1b-4dff-be28-17a6cf37c531", "type": "text"}], "vectors": [], "metadata": [], "allow_extra_metadata": false, "distribution": {"strategy": "overlap", "min_submitted": 1}, "mapping": null}

README.md

@@ -1,54 +1,193 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: status
-    dtype: string
-  - name: _server_id
-    dtype: string
-  - name: text
-    dtype: string
-  - name: label.suggestion
-    dtype:
-      class_label:
-        names:
-          '0': Business
-          '1': Sci/Tech
-          '2': Sports
-          '3': World
-  - name: label.suggestion.score
-    dtype: 'null'
-  - name: label.suggestion.agent
-    dtype: 'null'
-  - name: label.responses
-    list: string
-  - name: entities.responses
-    list:
-      list:
-      - name: end
-        dtype: int64
-      - name: label
-        dtype: string
-      - name: start
-        dtype: int64
-  - name: label.responses.users
-    list: string
-  - name: entities.responses.users
-    list: string
-  - name: entities.responses.status
-    list: string
-  - name: label.responses.status
-    list: string
-  splits:
-  - name: train
-    num_bytes: 40716625
-    num_examples: 120000
-  download_size: 24023694
-  dataset_size: 40716625
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+size_categories: 100K<n<1M
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+
+# Dataset Card for my_dataset
+
+
+
+
+
+
+
+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("Likies/my_dataset", 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("Likies/my_dataset")
+```
+
+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 | Markdown |
+| ---------- | ----- | ---- | -------- | -------- |
+| text | text | text | True | 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 | Classify the text: | label_selection | True | N/A | ['Business', 'Sci/Tech', 'Sports', 'World'] |
+| entities | Highlight all the entities in the text: | span | True | N/A | N/A |
+
+
+<!-- check length of metadata properties -->
+
+
+
+
+
+### Data Instances
+
+An example of a dataset instance in Argilla looks as follows:
+
+```json
+{
+    "_server_id": "0844d8e4-b9c0-4339-a011-08c137bf1a71",
+    "fields": {
+        "text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street\u0027s dwindling\\band of ultra-cynics, are seeing green again."
+    },
+    "id": "train_0",
+    "metadata": {},
+    "responses": {},
+    "status": "pending",
+    "suggestions": {
+        "label": {
+            "agent": null,
+            "score": null,
+            "value": "Business"
+        }
+    },
+    "vectors": {}
+}
+```
+
+While the same record in HuggingFace `datasets` looks as follows:
+
+```json
+{
+    "_server_id": "0844d8e4-b9c0-4339-a011-08c137bf1a71",
+    "entities.responses": null,
+    "entities.responses.status": null,
+    "entities.responses.users": null,
+    "id": "train_0",
+    "label.responses": null,
+    "label.responses.status": null,
+    "label.responses.users": null,
+    "label.suggestion": 0,
+    "label.suggestion.agent": null,
+    "label.suggestion.score": null,
+    "status": "pending",
+    "text": "Wall St. Bears Claw Back Into the Black (Reuters) Reuters - Short-sellers, Wall Street\u0027s dwindling\\band of ultra-cynics, are seeing green again."
+}
+```
+
+
+### 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]