Upload folder using huggingface_hub

.argilla/dataset.json

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+{
+  "id": "dbc95273-6f77-42bb-978a-606395dfca3e",
+  "name": "imdb-argilla-test",
+  "guidelines": null,
+  "allow_extra_metadata": true,
+  "status": "ready",
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "metadata": {
+    "repoId": "stanfordnlp/imdb",
+    "subset": "plain_text",
+    "split": "train",
+    "mapping": {
+      "fields": [
+        {
+          "source": "text",
+          "target": "text"
+        }
+      ],
+      "metadata": [],
+      "suggestions": []
+    },
+    "imported": "UI"
+  },
+  "workspace_id": "2a624869-1181-42f6-84f2-f6bcf2737fa7",
+  "last_activity_at": "2025-04-10T08:04:47.301259",
+  "inserted_at": "2025-04-10T07:33:47.131968",
+  "updated_at": "2025-04-10T07:33:48.911058"
+}

.argilla/settings.json

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+{
+  "guidelines": null,
+  "allow_extra_metadata": true,
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "fields": [
+    {
+      "id": "7572ab4f-2d27-4f70-86cf-8b0eb96a469c",
+      "name": "text",
+      "title": "text",
+      "required": false,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "dbc95273-6f77-42bb-978a-606395dfca3e",
+      "inserted_at": "2025-04-10T07:33:47.511024",
+      "updated_at": "2025-04-10T07:33:47.511024"
+    }
+  ],
+  "questions": [
+    {
+      "id": "eb2d5914-d709-4277-928f-0894c4d41432",
+      "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": "dbc95273-6f77-42bb-978a-606395dfca3e",
+      "inserted_at": "2025-04-10T07:33:47.872124",
+      "updated_at": "2025-04-10T07:33:47.872124"
+    },
+    {
+      "id": "11dc846b-58b7-401c-b774-878ad79e2605",
+      "name": "multi-label_1",
+      "title": "multi-label_1",
+      "description": null,
+      "required": true,
+      "settings": {
+        "type": "multi_label_selection",
+        "options": [
+          {
+            "value": "furniture",
+            "text": "furniture",
+            "description": null
+          },
+          {
+            "value": "electronics",
+            "text": "electronics",
+            "description": null
+          },
+          {
+            "value": "cuisines",
+            "text": "cuisines",
+            "description": null
+          },
+          {
+            "value": "others",
+            "text": "others",
+            "description": null
+          }
+        ],
+        "visible_options": null,
+        "options_order": "natural"
+      },
+      "dataset_id": "dbc95273-6f77-42bb-978a-606395dfca3e",
+      "inserted_at": "2025-04-10T07:33:48.209349",
+      "updated_at": "2025-04-10T07:33:48.209349"
+    },
+    {
+      "id": "102fe467-d0d1-43f3-b757-53d674f1c696",
+      "name": "rating_2",
+      "title": "rating_2",
+      "description": null,
+      "required": true,
+      "settings": {
+        "type": "rating",
+        "options": [
+          {
+            "value": 0
+          },
+          {
+            "value": 1
+          },
+          {
+            "value": 2
+          },
+          {
+            "value": 3
+          },
+          {
+            "value": 4
+          },
+          {
+            "value": 5
+          }
+        ]
+      },
+      "dataset_id": "dbc95273-6f77-42bb-978a-606395dfca3e",
+      "inserted_at": "2025-04-10T07:33:48.569098",
+      "updated_at": "2025-04-10T07:33:48.569098"
+    }
+  ],
+  "metadata": [],
+  "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: text
-    dtype: string
-  - name: label_0.responses
-    sequence: string
-  - name: label_0.responses.users
-    sequence: string
-  - name: label_0.responses.status
-    sequence: string
-  - name: multi-label_1.responses
-    sequence:
-      sequence: string
-  - name: multi-label_1.responses.users
-    sequence: string
-  - name: multi-label_1.responses.status
-    sequence: string
-  - name: rating_2.responses
-    sequence: int64
-  - name: rating_2.responses.users
-    sequence: string
-  - name: rating_2.responses.status
-    sequence: string
-  splits:
-  - name: train
-    num_bytes: 36202427
-    num_examples: 25000
-  download_size: 22348184
-  dataset_size: 36202427
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+
+# Dataset Card for imdb-argilla-test
+
+
+
+
+
+
+
+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("baksEtech/imdb-argilla-test", 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("baksEtech/imdb-argilla-test")
+```
+
+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 |
+| ---------- | ----- | ---- | -------- |
+| text | text | 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'] |
+| multi-label_1 | multi-label_1 | multi_label_selection | True | N/A | ['furniture', 'electronics', 'cuisines', 'others'] |
+| rating_2 | rating_2 | rating | True | N/A | [0, 1, 2, 3, 4, 5] |
+
+
+<!-- check length of metadata properties -->
+
+
+
+
+### 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]