Upload folder using huggingface_hub

.argilla/dataset.json

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+{"id": "99b73d6d-35b0-4a30-84e2-15c633ddb6ac", "inserted_at": "2025-10-13T04:52:00.419871", "updated_at": "2025-10-13T04:52:00.655504", "name": "my_dataset_1", "status": "ready", "guidelines": "These are some guidelines", "allow_extra_metadata": false, "distribution": {"strategy": "overlap", "min_submitted": 1}, "workspace_id": "aece7f87-7ff5-43c7-9f9c-8c167562dda8", "last_activity_at": "2025-10-13T04:52:00.655504"}

.argilla/settings.json

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+{"guidelines": "These are some guidelines", "questions": [{"id": "96e135f0-8ac7-453d-9014-073809065e34", "inserted_at": "2025-10-13T04:52:00.609546", "updated_at": "2025-10-13T04:52:00.609546", "name": "label", "settings": {"type": "label_selection", "options": [{"value": "neg", "text": "neg", "description": null}, {"value": "pos", "text": "pos", "description": null}], "visible_options": null}, "title": "label", "description": null, "required": true, "dataset_id": "99b73d6d-35b0-4a30-84e2-15c633ddb6ac", "type": "label_selection"}], "fields": [{"id": "71ab57d0-0da6-42fb-98df-816d19ee2958", "inserted_at": "2025-10-13T04:52:00.550032", "updated_at": "2025-10-13T04:52:00.550032", "name": "text", "settings": {"type": "text", "use_markdown": false}, "title": "text", "required": true, "description": null, "dataset_id": "99b73d6d-35b0-4a30-84e2-15c633ddb6ac", "type": "text"}], "vectors": [], "metadata": [], "allow_extra_metadata": false, "distribution": {"strategy": "overlap", "min_submitted": 1}, "mapping": null}

README.md

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 ---
-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': pos
-  - name: label.suggestion.score
-    dtype: 'null'
-  - name: label.suggestion.agent
-    dtype: 'null'
-  splits:
-  - name: train
-    num_bytes: 139698
-    num_examples: 97
-  download_size: 94090
-  dataset_size: 139698
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+size_categories: n<1K
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+
+# Dataset Card for imdb
+
+
+
+
+
+
+
+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("Sandhya2002/imdb", 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("Sandhya2002/imdb")
+```
+
+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 | label | label_selection | True | N/A | ['neg', 'pos'] |
+
+
+<!-- check length of metadata properties -->
+
+
+
+
+
+### Data Instances
+
+An example of a dataset instance in Argilla looks as follows:
+
+```json
+{
+    "_server_id": "710aae8c-eee0-4f82-86a6-06e33f1508fa",
+    "fields": {
+        "text": "This film was probably inspired by Godard\u0027s Masculin, f\u00e9minin and I urge you to see that film instead.\u003cbr /\u003e\u003cbr /\u003eThe film has two strong elements and those are, (1) the realistic acting (2) the impressive, undeservedly good, photo. Apart from that, what strikes me most is the endless stream of silliness. Lena Nyman has to be most annoying actress in the world. She acts so stupid and with all the nudity in this film,...it\u0027s unattractive. Comparing to Godard\u0027s film, intellectuality has been replaced with stupidity. Without going too far on this subject, I would say that follows from the difference in ideals between the French and the Swedish society.\u003cbr /\u003e\u003cbr /\u003eA movie of its time, and place. 2/10."
+    },
+    "id": "train[:100]_3",
+    "metadata": {},
+    "responses": {},
+    "status": "pending",
+    "suggestions": {
+        "label": {
+            "agent": null,
+            "score": null,
+            "value": "pos"
+        }
+    },
+    "vectors": {}
+}
+```
+
+While the same record in HuggingFace `datasets` looks as follows:
+
+```json
+{
+    "_server_id": "710aae8c-eee0-4f82-86a6-06e33f1508fa",
+    "id": "train[:100]_3",
+    "label.suggestion": 0,
+    "label.suggestion.agent": null,
+    "label.suggestion.score": null,
+    "status": "pending",
+    "text": "This film was probably inspired by Godard\u0027s Masculin, f\u00e9minin and I urge you to see that film instead.\u003cbr /\u003e\u003cbr /\u003eThe film has two strong elements and those are, (1) the realistic acting (2) the impressive, undeservedly good, photo. Apart from that, what strikes me most is the endless stream of silliness. Lena Nyman has to be most annoying actress in the world. She acts so stupid and with all the nudity in this film,...it\u0027s unattractive. Comparing to Godard\u0027s film, intellectuality has been replaced with stupidity. Without going too far on this subject, I would say that follows from the difference in ideals between the French and the Swedish society.\u003cbr /\u003e\u003cbr /\u003eA movie of its time, and place. 2/10."
+}
+```
+
+
+### 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
+
+These are some guidelines
+
+#### 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]