Upload folder using huggingface_hub
Browse files- .argilla/dataset.json +16 -0
- .argilla/settings.json +157 -0
- .argilla/version.json +3 -0
- README.md +150 -47
.argilla/dataset.json
ADDED
@@ -0,0 +1,16 @@
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{
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"id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"name": "techchefz-website-data-v8",
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"guidelines": "These are some guidelines.",
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"allow_extra_metadata": false,
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"status": "ready",
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"distribution": {
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"strategy": "overlap",
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"min_submitted": 1
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},
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"metadata": null,
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"workspace_id": "e5456095-355b-4c4f-b7b7-e0e4ae477374",
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"last_activity_at": "2025-02-11T10:10:34.700676",
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"inserted_at": "2025-02-11T10:10:33.645250",
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"updated_at": "2025-02-11T10:10:34.700676"
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}
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.argilla/settings.json
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{
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"guidelines": "These are some guidelines.",
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"allow_extra_metadata": false,
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"distribution": {
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"strategy": "overlap",
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"min_submitted": 1
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},
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"fields": [
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{
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"id": "624f3a25-c8ed-480f-837e-eff7f94ef2f3",
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"name": "content",
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"title": "content",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:33.832249",
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"updated_at": "2025-02-11T10:10:33.832249"
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},
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{
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"id": "9fe557c1-93ae-49a9-ae13-4a272c8c9b22",
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"name": "title",
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"title": "title",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:33.922402",
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"updated_at": "2025-02-11T10:10:33.922402"
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},
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{
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"id": "d23f8ba6-fe94-4ed0-b586-7e800f78beef",
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"name": "description",
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"title": "description",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:34.005903",
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"updated_at": "2025-02-11T10:10:34.005903"
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},
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{
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"id": "e74b7ccd-3a66-48c4-9530-dfc3361c084e",
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"name": "url",
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"title": "url",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:34.088104",
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"updated_at": "2025-02-11T10:10:34.088104"
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},
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{
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"id": "ee5f1735-2805-4a0a-944f-1fcb43ae5f82",
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"name": "source",
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"title": "source",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:34.172762",
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"updated_at": "2025-02-11T10:10:34.172762"
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},
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{
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"id": "07a5c520-8616-46ee-8e5d-4c0194ffc66a",
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"name": "ques1",
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"title": "ques1",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:34.258692",
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"updated_at": "2025-02-11T10:10:34.258692"
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},
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{
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"id": "8e1b9b0f-be8e-44d9-8fe5-21ec7303975b",
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"name": "ques2",
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"title": "ques2",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:34.346187",
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"updated_at": "2025-02-11T10:10:34.346187"
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},
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{
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"id": "7745470f-deca-474b-ae3c-455b544ba2ec",
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"name": "ques3",
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"title": "ques3",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:34.431435",
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"updated_at": "2025-02-11T10:10:34.431435"
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},
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{
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"id": "909e0a91-a127-408e-b79a-2bf3119b090d",
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"name": "sheetname",
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"title": "sheetname",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:34.522121",
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"updated_at": "2025-02-11T10:10:34.522121"
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}
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],
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"questions": [
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{
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"id": "010fd912-b82f-47e7-93be-d2e04f837b55",
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"name": "label",
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"title": "label",
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"description": null,
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"required": true,
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"settings": {
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"type": "label_selection",
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"options": [
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{
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"value": "yes",
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"text": "yes",
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"description": null
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},
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{
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"value": "no",
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"text": "no",
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"description": null
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}
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],
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"visible_options": null
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},
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"dataset_id": "d6c494e7-4335-48df-afc5-4c23f1bad945",
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"inserted_at": "2025-02-11T10:10:34.609645",
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"updated_at": "2025-02-11T10:10:34.609645"
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}
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],
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"metadata": [],
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"vectors": []
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}
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.argilla/version.json
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{
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"argilla": "2.6.0"
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}
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README.md
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---
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-
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- name: status
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dtype: string
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- name: inserted_at
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dtype: timestamp[us]
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- name: updated_at
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dtype: timestamp[us]
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- name: _server_id
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dtype: string
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- name: content
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dtype: string
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- name: title
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dtype: string
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- name: description
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dtype: string
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- name: url
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dtype: string
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- name: source
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dtype: string
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- name: ques1
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dtype: string
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- name: ques2
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dtype: string
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- name: ques3
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dtype: string
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- name: sheetname
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dtype: string
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- name: label.responses
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dtype: 'null'
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- name: label.responses.users
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dtype: 'null'
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- name: label.responses.status
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dtype: 'null'
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splits:
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- name: train
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num_bytes: 85857
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num_examples: 75
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download_size: 54866
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dataset_size: 85857
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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---
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---
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tags:
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- rlfh
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- argilla
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- human-feedback
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---
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# Dataset Card for techchefz-website-data-v8
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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).
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## Using this dataset with Argilla
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To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
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```python
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import argilla as rg
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ds = rg.Dataset.from_hub("Shashwat13333/techchefz-website-data-v8", settings="auto")
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```
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This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
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## Using this dataset with `datasets`
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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:
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```python
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from datasets import load_dataset
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ds = load_dataset("Shashwat13333/techchefz-website-data-v8")
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```
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This will only load the records of the dataset, but not the Argilla settings.
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## Dataset Structure
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This dataset repo contains:
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* 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`.
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* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
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* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.
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The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
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### Fields
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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.
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| Field Name | Title | Type | Required |
|
58 |
+
| ---------- | ----- | ---- | -------- |
|
59 |
+
| content | content | text | True |
|
60 |
+
| title | title | text | True |
|
61 |
+
| description | description | text | True |
|
62 |
+
| url | url | text | True |
|
63 |
+
| source | source | text | True |
|
64 |
+
| ques1 | ques1 | text | True |
|
65 |
+
| ques2 | ques2 | text | True |
|
66 |
+
| ques3 | ques3 | text | True |
|
67 |
+
| sheetname | sheetname | text | True |
|
68 |
+
|
69 |
+
|
70 |
+
### Questions
|
71 |
+
|
72 |
+
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.
|
73 |
+
|
74 |
+
| Question Name | Title | Type | Required | Description | Values/Labels |
|
75 |
+
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
|
76 |
+
| label | label | label_selection | True | N/A | ['yes', 'no'] |
|
77 |
+
|
78 |
+
|
79 |
+
<!-- check length of metadata properties -->
|
80 |
+
|
81 |
+
|
82 |
+
|
83 |
+
|
84 |
+
### Data Splits
|
85 |
+
|
86 |
+
The dataset contains a single split, which is `train`.
|
87 |
+
|
88 |
+
## Dataset Creation
|
89 |
+
|
90 |
+
### Curation Rationale
|
91 |
+
|
92 |
+
[More Information Needed]
|
93 |
+
|
94 |
+
### Source Data
|
95 |
+
|
96 |
+
#### Initial Data Collection and Normalization
|
97 |
+
|
98 |
+
[More Information Needed]
|
99 |
+
|
100 |
+
#### Who are the source language producers?
|
101 |
+
|
102 |
+
[More Information Needed]
|
103 |
+
|
104 |
+
### Annotations
|
105 |
+
|
106 |
+
#### Annotation guidelines
|
107 |
+
|
108 |
+
These are some guidelines.
|
109 |
+
|
110 |
+
#### Annotation process
|
111 |
+
|
112 |
+
[More Information Needed]
|
113 |
+
|
114 |
+
#### Who are the annotators?
|
115 |
+
|
116 |
+
[More Information Needed]
|
117 |
+
|
118 |
+
### Personal and Sensitive Information
|
119 |
+
|
120 |
+
[More Information Needed]
|
121 |
+
|
122 |
+
## Considerations for Using the Data
|
123 |
+
|
124 |
+
### Social Impact of Dataset
|
125 |
+
|
126 |
+
[More Information Needed]
|
127 |
+
|
128 |
+
### Discussion of Biases
|
129 |
+
|
130 |
+
[More Information Needed]
|
131 |
+
|
132 |
+
### Other Known Limitations
|
133 |
+
|
134 |
+
[More Information Needed]
|
135 |
+
|
136 |
+
## Additional Information
|
137 |
+
|
138 |
+
### Dataset Curators
|
139 |
+
|
140 |
+
[More Information Needed]
|
141 |
+
|
142 |
+
### Licensing Information
|
143 |
+
|
144 |
+
[More Information Needed]
|
145 |
+
|
146 |
+
### Citation Information
|
147 |
+
|
148 |
+
[More Information Needed]
|
149 |
+
|
150 |
+
### Contributions
|
151 |
+
|
152 |
+
[More Information Needed]
|