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.argilla/dataset.json

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+{
+  "id": "950c0cbe-7412-4af6-94e6-64d49b44a1ee",
+  "name": "imdb-with-custom",
+  "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": [
+        {
+          "source": "label",
+          "target": "label"
+        }
+      ]
+    },
+    "imported": "UI"
+  },
+  "workspace_id": "9b40ede0-87d5-4b20-9299-690c0c385c66",
+  "last_activity_at": "2024-12-02T14:40:52.372368",
+  "inserted_at": "2024-11-29T12:59:35.501032",
+  "updated_at": "2024-11-29T12:59:35.580005"
+}

.argilla/settings.json

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+{
+  "guidelines": null,
+  "allow_extra_metadata": true,
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "fields": [
+    {
+      "id": "4b7fd98b-32bb-4296-81ab-3dbe9735d833",
+      "name": "text",
+      "title": "text",
+      "required": false,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "950c0cbe-7412-4af6-94e6-64d49b44a1ee",
+      "inserted_at": "2024-11-29T12:59:35.540379",
+      "updated_at": "2024-11-29T12:59:35.540379"
+    },
+    {
+      "id": "1e1b8134-5d83-4869-a55f-08de196c6fc4",
+      "name": "custom",
+      "title": "Custom",
+      "required": false,
+      "settings": {
+        "type": "custom",
+        "template": "hello",
+        "advanced_mode": false
+      },
+      "dataset_id": "950c0cbe-7412-4af6-94e6-64d49b44a1ee",
+      "inserted_at": "2024-11-29T13:02:14.928389",
+      "updated_at": "2024-11-29T13:02:14.928389"
+    }
+  ],
+  "questions": [
+    {
+      "id": "0da13c6b-a60d-41b1-b0f3-571c17244e20",
+      "name": "label",
+      "title": "label",
+      "description": null,
+      "required": true,
+      "settings": {
+        "type": "label_selection",
+        "options": [
+          {
+            "value": "neg",
+            "text": "neg",
+            "description": null
+          },
+          {
+            "value": "pos",
+            "text": "pos",
+            "description": null
+          }
+        ],
+        "visible_options": null
+      },
+      "dataset_id": "950c0cbe-7412-4af6-94e6-64d49b44a1ee",
+      "inserted_at": "2024-11-29T12:59:35.560686",
+      "updated_at": "2024-11-29T12:59:35.560686"
+    }
+  ],
+  "metadata": [],
+  "vectors": []
+}

.argilla/version.json

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+{
+  "argilla": "2.6.0dev0"
+}

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: custom
-    struct:
-    - name: one
-      dtype: string
-    - name: three
-      dtype: string
-    - name: two
-      dtype: string
-  - name: label.responses
-    sequence: string
-  - name: label.responses.users
-    sequence: string
-  - name: label.responses.status
-    sequence: string
-  splits:
-  - name: train
-    num_bytes: 14023070
-    num_examples: 10000
-  download_size: 8800811
-  dataset_size: 14023070
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+
+# Dataset Card for imdb-with-custom
+
+
+
+
+
+
+
+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("jfcalvo/imdb-with-custom", 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("jfcalvo/imdb-with-custom")
+```
+
+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 |
+| custom | Custom | custom | 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 | [] |
+
+
+<!-- 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]