Upload folder using huggingface_hub

.argilla/dataset.json

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+{
+  "id": "dd81abea-e50b-4f8f-b127-7cd47e43cfd8",
+  "name": "advanced_audio_dataset",
+  "guidelines": "These are some guidelines.",
+  "allow_extra_metadata": false,
+  "status": "ready",
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "metadata": null,
+  "workspace_id": "8c9082cb-f67a-41af-a2e7-8a62baf8196e",
+  "last_activity_at": "2025-04-30T10:50:53.913883",
+  "inserted_at": "2025-04-30T10:46:02.934237",
+  "updated_at": "2025-04-30T10:46:03.511515"
+}

.argilla/settings.json

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+{
+  "guidelines": "These are some guidelines.",
+  "allow_extra_metadata": false,
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "fields": [
+    {
+      "id": "6d595bd1-9cce-4778-a4fd-b3f417783412",
+      "name": "audio",
+      "title": "Audio Player",
+      "required": true,
+      "settings": {
+        "type": "custom",
+        "template": "\n<div id=\"audio-container\"></div>\n<script>\n// Helper function: Write a string to a DataView.\nfunction writeString(view, offset, string) {\n  for (var i = 0; i < string.length; i++) {\n    view.setUint8(offset + i, string.charCodeAt(i));\n  }\n}\n// Convert an array of floats (normalized -1 to 1) to 16-bit PCM.\nfunction floatTo16BitPCM(output, offset, input) {\n  for (var i = 0; i < input.length; i++, offset += 2) {\n    var s = Math.max(-1, Math.min(1, input[i]));\n    output.setInt16(offset, s < 0 ? s * 0x8000 : s * 0x7FFF, true);\n  }\n}\n// Convert a float array and sample rate into a WAV file buffer.\nfunction arrayToWav(samples, sampleRate) {\n  var buffer = new ArrayBuffer(44 + samples.length * 2);\n  var view = new DataView(buffer);\n  writeString(view, 0, 'RIFF');\n  view.setUint32(4, 36 + samples.length * 2, true);\n  writeString(view, 8, 'WAVE');\n  writeString(view, 12, 'fmt ');\n  view.setUint32(16, 16, true);\n  view.setUint16(20, 1, true);\n  view.setUint16(22, 1, true);\n  view.setUint32(24, sampleRate, true);\n  view.setUint32(28, sampleRate * 2, true);\n  view.setUint16(32, 2, true);\n  view.setUint16(34, 16, true);\n  writeString(view, 36, 'data');\n  view.setUint32(40, samples.length * 2, true);\n  floatTo16BitPCM(view, 44, samples);\n  return buffer;\n}\n\n// Advanced mode: process the raw audio array from record.fields.audio.array\nvar audioData = record.fields.audio.array;\nvar sampleRate = record.fields.audio.sampling_rate || 16000;\nif (audioData && audioData.length > 0) {\n  var wavBuffer = arrayToWav(audioData, sampleRate);\n  var blob = new Blob([wavBuffer], { type: 'audio/wav' });\n  var audioUrl = URL.createObjectURL(blob);\n  var audioElem = document.createElement('audio');\n  audioElem.controls = true;\n  audioElem.autoplay = true; // Automatically play on render.\n  audioElem.src = audioUrl;\n  document.getElementById('audio-container').appendChild(audioElem);\n} else {\n  document.getElementById('audio-container').innerHTML = \"No audio data available.\";\n}\n</script>\n",
+        "advanced_mode": true
+      },
+      "dataset_id": "dd81abea-e50b-4f8f-b127-7cd47e43cfd8",
+      "inserted_at": "2025-04-30T10:46:03.277274",
+      "updated_at": "2025-04-30T10:46:03.277274"
+    }
+  ],
+  "questions": [
+    {
+      "id": "109ca1f4-24f5-4f8b-bdb0-0a75e5f1187a",
+      "name": "genre",
+      "title": "genre",
+      "description": null,
+      "required": true,
+      "settings": {
+        "type": "label_selection",
+        "options": [
+          {
+            "value": "homme",
+            "text": "homme",
+            "description": null
+          },
+          {
+            "value": "femme",
+            "text": "femme",
+            "description": null
+          }
+        ],
+        "visible_options": null
+      },
+      "dataset_id": "dd81abea-e50b-4f8f-b127-7cd47e43cfd8",
+      "inserted_at": "2025-04-30T10:46:03.396194",
+      "updated_at": "2025-04-30T10:46:03.396194"
+    }
+  ],
+  "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: audio
-    struct:
-    - name: array
-      sequence: float64
-    - name: path
-      dtype: string
-    - name: sampling_rate
-      dtype: int64
-  - name: genre.responses
-    sequence: string
-  - name: genre.responses.users
-    sequence: string
-  - name: genre.responses.status
-    sequence: string
-  splits:
-  - name: train
-    num_bytes: 11789816
-    num_examples: 10
-  download_size: 3252766
-  dataset_size: 11789816
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+
+# Dataset Card for advanced_audio_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("baksEtech/advanced_audio_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("baksEtech/advanced_audio_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 |
+| ---------- | ----- | ---- | -------- |
+| audio | Audio Player | custom | True |
+
+
+### 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 |
+| ------------- | ----- | ---- | -------- | ----------- | ------------- |
+| genre | genre | label_selection | True | N/A | ['homme', 'femme'] |
+
+
+<!-- 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
+
+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]