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godivyam/business-companies-news-dataset | godivyam | 2023-11-26T10:46:21Z | 0 | 0 | null | [
"license:mit",
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license: mit
---
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license: mit
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---
# Dataset Card for "hh-rlhf-harmyes"
Original Dataset: https://huggingface.co/datasets/Anthropic/hh-rlhf
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nookbe/Handelsgesetzbuch_HGB | nookbe | 2023-11-26T11:53:18Z | 0 | 0 | null | [
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] | 2023-11-26T11:53:18Z | 2023-11-26T11:48:25.000Z | 2023-11-26T11:48:25 | ---
license: mit
task_categories:
- text-classification
language:
- de
tags:
- legal
pretty_name: HGB
size_categories:
- 1K<n<10K
---
license: mit
task_categories:
- text-classification
language:
- de
tags:
- legal
pretty_name: HGB
size_categories:
- 1K<n<10K
---
# German HGB Law Dataset (Handelsgesetzbuch)
## Dataset Description
- **Date of Last Paragraph Update:** April 2023
- **Dataset Guarantee:** The dataset is provided "as is," and there is no guarantee for the correctness or completeness of the data.
### Dataset Summary
The HGB Law Dataset contains legal text from the German Commercial Code (Handelsgesetzbuch - HGB). It focuses on the general principles of German commercial law, and the dataset is designed for tasks related to legal text analysis.
## Dataset Structure
### Data Instances
A typical data point in the dataset comprises a legal paragraph and its corresponding text. For example:
```json
{
'paragraph': '§ 1 Handelsstand',
'text': 'Wer ein Handelsgewerbe betreibt, ist Kaufmann.'
}
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laiyer/image-prompt-injection | laiyer | 2023-11-26T11:52:01Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
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license: apache-2.0
---
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JestemKamil/NexiaBot-Dataset | JestemKamil | 2023-11-26T12:33:09Z | 0 | 0 | null | [
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yasosa/testulan | yasosa | 2023-11-26T12:34:25Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
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license: apache-2.0
---
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celsowm/meu_site_juridico_perguntas_e_respostas | celsowm | 2023-11-26T12:49:56Z | 0 | 0 | null | [
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---
# Dataset Card for "meu_site_juridico_perguntas_e_respostas"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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license: openrail
---
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AhmadMustafa/Urdu-Instruct-News-Article-Generation | AhmadMustafa | 2023-11-26T16:43:42Z | 0 | 1 | null | [
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:100K<n<1M",
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dataset_info:
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task_categories:
- text-generation
- text2text-generation
language:
- ur
pretty_name: Instruct News Article Generation Urdu
size_categories:
- 100K<n<1M
---
# Dataset Card for "Urdu-Instruct-News-Article-Generation"
This Dataset is converted from the [original dataset](https://data.mendeley.com/datasets/834vsxnb99/3) by Khalid Hussain, Nimra Mughal, Irfan Ali, Saif Hassan, Sher Muhammad Daudpota.
## Task:
Generate the News Article from the given headline.
## Split Size:
- train: 100674
- test: 11187
## Prompt Template (In Urdu):
Random.choice b.w these 2
```
[ "اس دی گی ایک خبر سے متعلق ایک مضمون لکھیں۔
خبر: {}",
"یہ خبر جو {} سے تعلق رکھتی ہے، اس پر ایک مضمون لکھیں۔
خبر: {}"
]
```
<b>Translation</b>:
```
1. Write an article from the given news.
news: {}
2. Given the news belonging to category {}, write an article on it.
news: {}
```
## Completion Template (In Urdu)
```
جی ضرور، یہ رہا آپ کی خبر سے متعلق ایک مضمون:
{}
```
<b>Translation</b>:
```
Sure, here is the article related to the given news
{}
``` | [
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0.4329321682453155... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
AhmadMustafa/Urdu-Instruct-News-Category-Classification | AhmadMustafa | 2023-11-26T17:13:00Z | 0 | 0 | null | [
"task_categories:text-classification",
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:100K<n<1M",
"language:ur",
"region:us"
] | 2023-11-26T17:13:00Z | 2023-11-26T15:35:37.000Z | 2023-11-26T15:35:37 | ---
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 250236730.2471639
num_examples: 100674
- name: test
num_bytes: 27806566.75283611
num_examples: 11187
download_size: 115812030
dataset_size: 278043297
task_categories:
- text-classification
- text-generation
- text2text-generation
language:
- ur
pretty_name: Instruct News Category Classification Urdu
size_categories:
- 100K<n<1M
---
# Dataset Card for "Urdu-Instruct-News-Category-Classification"
This Dataset is converted from the [original dataset](https://data.mendeley.com/datasets/834vsxnb99/3) by Khalid Hussain, Nimra Mughal, Irfan Ali, Saif Hassan, Sher Muhammad Daudpota.
## Task:
Generate the News Paragraph, and classify the news category from it.
### Categories:
- We are using both English and Urdu Categories based on random selection. Here is the mapping `{'Sports': 'کھیل', 'Entertainment': 'تفریح', 'Business & Economics':'کاروبار و معیشت', 'Science & Technology': 'سائنس اور ٹیکنالوجی'}`
```
Sports 22502
کھیل 22327
Entertainment 17498
تفریح 17403
Business & Economics 12084
کاروبار و معیشت 12047
Science & Technology 4017
سائنس اور ٹیکنالوجی 3982
```
This plot can help understand the distribution better.
## Split Size:
- train: 100674
- test: 11187
## Prompt Template (In Urdu):
Random.choice b.w these 2
```
["""اس اردو پیراگراف (خبروں) کو ایک درجہ (کیٹیگری) میں بیان کریں
پیراگراف: {}""",
"""دیے گے جملوں کو ایک لفظ یا درجہ (کیٹگری) میں بیان کریں.
جملے: {}"""]
```
<b>Translation</b>:
```
1. Convert this urdu paragraph (news) to a category
paragraph: {}
2. Classify the given sentences into a single category
sentences: {}
```
## Completion Template (In Urdu)
```
جی ضرور، یہ رہا آپ کے پیراگراف کا درجہ (کیٹگری) میں:
{}
```
<b>Translation</b>:
```
Sure, here is the category of your given paragraph.
{}
``` | [
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0.44536697864532... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
AhmadMustafa/Urdu-Instruct-News-Headline-Generation | AhmadMustafa | 2023-11-26T16:36:46Z | 0 | 0 | null | [
"task_categories:text-generation",
"task_categories:summarization",
"size_categories:100K<n<1M",
"language:ur",
"region:us"
] | 2023-11-26T16:36:46Z | 2023-11-26T15:40:27.000Z | 2023-11-26T15:40:27 | ---
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 257468711.89508408
num_examples: 100674
- name: test
num_bytes: 28610192.10491592
num_examples: 11187
download_size: 0
dataset_size: 286078904
task_categories:
- text-generation
- summarization
language:
- ur
pretty_name: Urdu Instruct News Headline Generation
size_categories:
- 100K<n<1M
---
# Dataset Card for "Urdu-Instruct-News-Headline-Generation"
This Dataset is converted from the [original dataset](https://data.mendeley.com/datasets/834vsxnb99/3) by Khalid Hussain, Nimra Mughal, Irfan Ali, Saif Hassan, Sher Muhammad Daudpota.
## Task:
Generate the News Headline from the given News.
## Split Size:
- train: 100674
- test: 11187
## Prompt Template (In Urdu):
Random.choice b.w these 2
```
["اس اردو پیراگراف (خبروں) کو ایک جملے میں خلاصہ بیان کریں
پیراگراف: {}",
"دیے گے جملوں کو ایک جملے میں خلاصہ بیان کریں.
جملے: {}"
]
```
<b>Translation</b>:
```
1. Tell the summary of the given paragraph in 1 sentence
paragraph: {}
2. Summarize the given sentences into 1 sentence
sentences: {}
```
## Completion Template (In Urdu)
```
جی ضرور، یہ رہا آپ کے پیراگراف کا خلاصہ ایک جملہ میں:
{}
```
<b>Translation</b>:
```
Sure, here is the summary of the given sentences
{}
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ezipe/lichess-2023-janoct | ezipe | 2023-11-26T23:23:36Z | 0 | 0 | null | [
"region:us"
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Gabriel1322/jotase | Gabriel1322 | 2023-11-26T15:58:33Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T15:58:33Z | 2023-11-26T15:55:24.000Z | 2023-11-26T15:55:24 | ---
license: openrail
---
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vilm/llava-hermes-fncall | vilm | 2023-11-27T12:43:31Z | 0 | 0 | null | [
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chrominancedesign/hf | chrominancedesign | 2023-11-26T16:14:06Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-26T16:14:06Z | 2023-11-26T16:14:06.000Z | 2023-11-26T16:14:06 | ---
license: apache-2.0
---
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xFrisky02/EnergiX | xFrisky02 | 2023-11-26T16:22:16Z | 0 | 0 | null | [
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vilm/GRIT-150K | vilm | 2023-11-27T06:44:56Z | 0 | 0 | null | [
"region:us"
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Pablao0948/Leozinho | Pablao0948 | 2023-11-26T16:58:00Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T16:58:00Z | 2023-11-26T16:57:07.000Z | 2023-11-26T16:57:07 | ---
license: openrail
---
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Kauasido/PACKMCDALESTE | Kauasido | 2023-11-26T17:49:21Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T17:49:21Z | 2023-11-26T17:47:37.000Z | 2023-11-26T17:47:37 | ---
license: openrail
---
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isabelabr/raffamoreira | isabelabr | 2023-11-26T18:00:35Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T18:00:35Z | 2023-11-26T18:00:01.000Z | 2023-11-26T18:00:01 | ---
license: openrail
---
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lhallee/Thermostability_fold | lhallee | 2023-11-26T18:05:33Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T18:05:33Z | 2023-11-26T18:05:27.000Z | 2023-11-26T18:05:27 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
- split: test
path: data/test-*
dataset_info:
features:
- name: seqs
dtype: string
- name: labels
dtype: float64
splits:
- name: train
num_bytes: 5920444
num_examples: 5056
- name: valid
num_bytes: 739542
num_examples: 639
- name: test
num_bytes: 1574670
num_examples: 1336
download_size: 6866906
dataset_size: 8234656
---
# Dataset Card for "Thermostability_fold"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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onlycaps/flickr8k-sau-pace-annotated | onlycaps | 2023-11-26T18:30:31Z | 0 | 0 | null | [
"task_categories:image-classification",
"license:mit",
"region:us"
] | 2023-11-26T18:30:31Z | 2023-11-26T18:20:45.000Z | 2023-11-26T18:20:45 | ---
license: mit
task_categories:
- image-classification
---
# Annotation
Annotated this [dataset](https://www.kaggle.com/datasets/srbhshinde/flickr8k-sau) by clasifying the images into slow, medium or fast depending on the suitable paced background music. | [
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AntibodyGeneration/sabdab_joint_sequences_uniprot | AntibodyGeneration | 2023-11-26T18:25:32Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-26T18:25:32Z | 2023-11-26T18:22:31.000Z | 2023-11-26T18:22:31 | ---
license: apache-2.0
---
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Rishabh621/Rishabh_voicewover | Rishabh621 | 2023-11-26T18:34:18Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-26T18:34:18Z | 2023-11-26T18:34:18.000Z | 2023-11-26T18:34:18 | ---
license: apache-2.0
---
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Arabic-Clip/mscoco_captions_ViT-B-16-SigLIP-512 | Arabic-Clip | 2023-11-26T18:43:35Z | 0 | 0 | null | [
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isabelabr/bcraffthebox | isabelabr | 2023-11-26T18:39:43Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T18:39:43Z | 2023-11-26T18:39:24.000Z | 2023-11-26T18:39:24 | ---
license: openrail
---
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vfffffff/fvfd | vfffffff | 2023-11-26T18:42:59Z | 0 | 0 | null | [
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Vergilzx8/mmmmmm | Vergilzx8 | 2023-11-26T18:48:27Z | 0 | 0 | null | [
"license:unknown",
"region:us"
] | 2023-11-26T18:48:27Z | 2023-11-26T18:48:27.000Z | 2023-11-26T18:48:27 | ---
license: unknown
---
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mespinosami/elephants | mespinosami | 2023-11-26T19:16:36Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T19:16:36Z | 2023-11-26T18:53:42.000Z | 2023-11-26T18:53:42 | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': eles
'1': no_eles
splits:
- name: train
num_bytes: 14514122908.549025
num_examples: 159283
- name: test
num_bytes: 3662606794.077976
num_examples: 39821
download_size: 17959333418
dataset_size: 18176729702.627
---
# Dataset Card for "elephants"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Trollator/mcigu | Trollator | 2023-11-26T18:57:56Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T18:57:56Z | 2023-11-26T18:57:22.000Z | 2023-11-26T18:57:22 | ---
license: openrail
---
| [
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Rutson/DreamAcademy | Rutson | 2023-11-26T19:21:43Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T19:21:43Z | 2023-11-26T19:16:10.000Z | 2023-11-26T19:16:10 | Entry not found | [
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Pablao0948/Austin_Mahonne | Pablao0948 | 2023-11-26T19:20:29Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T19:20:29Z | 2023-11-26T19:19:55.000Z | 2023-11-26T19:19:55 | ---
license: openrail
---
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aatherton2024/ds_attemp_many | aatherton2024 | 2023-11-26T19:24:00Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T19:24:00Z | 2023-11-26T19:23:29.000Z | 2023-11-26T19:23:29 | ---
dataset_info:
features:
- name: image
dtype: image
- name: classification
dtype: string
splits:
- name: train
num_bytes: 2560750.0
num_examples: 5
download_size: 1700353
dataset_size: 2560750.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
| [
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Yoshkeen/qdb_one_line | Yoshkeen | 2023-11-26T19:25:11Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T19:25:11Z | 2023-11-26T19:23:37.000Z | 2023-11-26T19:23:37 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validate
path: data/validate-*
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 284092483.6629115
num_examples: 424085
- name: test
num_bytes: 35511811.66854428
num_examples: 53011
- name: validate
num_bytes: 35511811.66854428
num_examples: 53011
download_size: 187982407
dataset_size: 355116107.00000006
---
# Dataset Card for "qdb_one_line"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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islamrokon/evaluation | islamrokon | 2023-11-26T19:43:43Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T19:43:43Z | 2023-11-26T19:29:29.000Z | 2023-11-26T19:29:29 | Entry not found | [
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Hidromaniaco/hwei | Hidromaniaco | 2023-11-26T19:36:30Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T19:36:30Z | 2023-11-26T19:29:53.000Z | 2023-11-26T19:29:53 | ---
license: openrail
---
| [
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Lucasybp/dataset | Lucasybp | 2023-11-26T19:54:18Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T19:54:18Z | 2023-11-26T19:53:31.000Z | 2023-11-26T19:53:31 | Entry not found | [
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sswt/stanford-act-mooc | sswt | 2023-11-27T08:25:13Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T08:25:13Z | 2023-11-26T19:58:55.000Z | 2023-11-26T19:58:55 | # Social Network: MOOC User Action Dataset
[Link to original dataset]((https://snap.stanford.edu/data/act-mooc.html))
The MOOC user action dataset represents the actions taken by users on a popular MOOC platform. The actions have attributes and timestamps. Additionally, each action has a binary label, representing whether the user dropped-out of the course after this action, i.e., whether this is last action of the user.
The dataset have been generated as part of the research project on advanced user modeling and recommender systems.
Original dataset had 3 distinct csv files, they are joined to a single file here.
Columns:
* ACTIONID: a unique id for each action.
* USERID: a unique id for each user.
* TARGETID: a unique id for each target activity.
* FEATUREx: a feature value associated with the action. Total four in count, making it a 4-dimensional feature vector.
* TIMESTAMP: timestamp for the action in seconds from the beginning.
* LABEL: a binary label indicating whether the student drops-out after the action. The value is 1 for drop-out actions, 0 otherwise. | [
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AppleHarem/ch_en_arknights | AppleHarem | 2023-11-26T20:30:48Z | 0 | 0 | null | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2023-11-26T20:30:48Z | 2023-11-26T20:29:58.000Z | 2023-11-26T20:29:58 | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of ch'en (Arknights)
This is the dataset of ch'en (Arknights), containing 200 images and their tags.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).([LittleAppleWebUI](https://github.com/LittleApple-fp16/LittleAppleWebUI))
| Name | Images | Download | Description |
|:----------------|---------:|:----------------------------------------|:-----------------------------------------------------------------------------------------|
| raw | 200 | [Download](dataset-raw.zip) | Raw data with meta information. |
| raw-stage3 | 490 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. |
| raw-stage3-eyes | 605 | [Download](dataset-raw-stage3-eyes.zip) | 3-stage cropped (with eye-focus) raw data with meta information. |
| 384x512 | 200 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. |
| 512x704 | 200 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. |
| 640x880 | 200 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. |
| stage3-640 | 490 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. |
| stage3-800 | 490 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. |
| stage3-p512-640 | 339 | [Download](dataset-stage3-p512-640.zip) | 3-stage cropped dataset with the area not less than 512x512 pixels. |
| stage3-eyes-640 | 605 | [Download](dataset-stage3-eyes-640.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 640 pixels. |
| stage3-eyes-800 | 605 | [Download](dataset-stage3-eyes-800.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 800 pixels. |
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HossainRabby/UpdatedDataset | HossainRabby | 2023-11-28T18:25:11Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T18:25:11Z | 2023-11-26T20:30:35.000Z | 2023-11-26T20:30:35 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 72929903.08721887
num_examples: 14766
- name: test
num_bytes: 8104968.91278113
num_examples: 1641
download_size: 26912462
dataset_size: 81034872.0
---
# Dataset Card for "hii"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Gabriel1322/lucasdataset | Gabriel1322 | 2023-11-26T20:42:42Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T20:42:42Z | 2023-11-26T20:42:07.000Z | 2023-11-26T20:42:07 | ---
license: openrail
---
| [
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syntaxnoob/weather-prediction-prototype-aws | syntaxnoob | 2023-11-26T21:34:00Z | 0 | 0 | null | [
"size_categories:100K<n<1M",
"license:unlicense",
"region:us"
] | 2023-11-26T21:34:00Z | 2023-11-26T20:47:42.000Z | 2023-11-26T20:47:42 | ---
license: unlicense
size_categories:
- 100K<n<1M
---
# Weather prediction prototype database.
This database was made using data provided by KMI.
This database will only be used to train a prototype.
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **KMI**
## Dataset Structure
Normalized columns:
- timestamp
- air_pressure
- relative_humidity
- precipitation
- wind_speed
- wind_direction
More information about these columns can be found in the `information_10min.txt` file.
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
| [
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Tony-Yuan/TheElements | Tony-Yuan | 2023-11-27T03:05:55Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2023-11-27T03:05:55Z | 2023-11-26T20:52:53.000Z | 2023-11-26T20:52:53 | ---
license: apache-2.0
configs:
- config_name: default
data_files:
- split: train
path:
- "train.csv"
---
This is a GPT-4 generated question-and-answer dataset based on [The Elements](https://www.amazon.com/Elements-Visual-Exploration-Every-Universe/dp/1579128955/) by [Theodore Gray](https://home.theodoregray.com/).
| [
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VictorHProtogen/Amigos | VictorHProtogen | 2023-11-26T22:08:30Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T22:08:30Z | 2023-11-26T20:56:53.000Z | 2023-11-26T20:56:53 | ---
license: openrail
---
| [
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Arwa0/t2img_300_tar | Arwa0 | 2023-11-26T21:04:04Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T21:04:04Z | 2023-11-26T21:02:58.000Z | 2023-11-26T21:02:58 | Entry not found | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Erynan/1k_deon_util | Erynan | 2023-11-26T21:22:55Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T21:22:55Z | 2023-11-26T21:17:35.000Z | 2023-11-26T21:17:35 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1499818
num_examples: 2000
download_size: 259937
dataset_size: 1499818
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
| [
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-0.04782580211758613... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
DZN222/lucasdataset | DZN222 | 2023-11-26T21:21:20Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T21:21:20Z | 2023-11-26T21:21:02.000Z | 2023-11-26T21:21:02 | ---
license: openrail
---
| [
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Erynan/1k_deon_util_shuffled | Erynan | 2023-11-26T21:23:07Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T21:23:07Z | 2023-11-26T21:23:05.000Z | 2023-11-26T21:23:05 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
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num_bytes: 1499818
num_examples: 2000
download_size: 259937
dataset_size: 1499818
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
| [
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0.49436280131340027,
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0.05056314915418625,
0.5793651342391968,
0.740013837814331,
-0.6508103013038635,
-0.23783960938453674,
-0.7102248668670654,
-0.04782580211758613... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
DZN222/morador | DZN222 | 2023-11-26T21:33:49Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T21:33:49Z | 2023-11-26T21:33:35.000Z | 2023-11-26T21:33:35 | ---
license: openrail
---
| [
-0.12853369116783142,
-0.18616779148578644,
0.6529126167297363,
0.49436280131340027,
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0.05056314915418625,
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0.740013837814331,
-0.6508103013038635,
-0.23783960938453674,
-0.7102248668670654,
-0.04782580211758613... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Cordmail/reddit-FemaleDatingStrategy-unpopular | Cordmail | 2023-11-26T23:19:46Z | 0 | 0 | null | [
"region:us"
] | 2023-11-26T23:19:46Z | 2023-11-26T21:38:20.000Z | 2023-11-26T21:38:20 | Entry not found | [
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-0.9104475975036621,
0.5715674161911011,
-... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
tasksource/feasibilityQA | tasksource | 2023-11-26T21:48:54Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | 2023-11-26T21:48:54Z | 2023-11-26T21:46:10.000Z | 2023-11-26T21:46:10 | ---
license: mit
---
| [
-0.1285335123538971,
-0.1861683875322342,
0.6529128551483154,
0.49436232447624207,
-0.19319400191307068,
0.23607441782951355,
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0.05056373029947281,
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0.7400146722793579,
-0.650810182094574,
-0.23784008622169495,
-0.7102247476577759,
-0.0478255338966846... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
DZN222/lucas | DZN222 | 2023-11-26T21:56:12Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | 2023-11-26T21:56:12Z | 2023-11-26T21:55:11.000Z | 2023-11-26T21:55:11 | ---
license: openrail
---
| [
-0.1285335123538971,
-0.1861683875322342,
0.6529128551483154,
0.49436232447624207,
-0.19319400191307068,
0.23607441782951355,
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0.05056373029947281,
0.5793656706809998,
0.7400146722793579,
-0.650810182094574,
-0.23784008622169495,
-0.7102247476577759,
-0.0478255338966846... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
BangumiBase/greatpretender | BangumiBase | 2023-11-27T00:43:49Z | 0 | 0 | null | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | 2023-11-27T00:43:49Z | 2023-11-26T21:59:38.000Z | 2023-11-26T21:59:38 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Great Pretender
This is the image base of bangumi Great Pretender, we detected 50 characters, 3820 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 178 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 20 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 647 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 471 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 86 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 79 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 80 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 100 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 110 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 116 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 48 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 35 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 58 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 23 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 30 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 61 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 33 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 59 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 132 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 24 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 9 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 44 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 25 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 42 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 25 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 25 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 83 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 14 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 265 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 16 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 16 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 24 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 16 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 22 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 38 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 37 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 7 | [Download](36/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 37 | 18 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 40 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 15 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 281 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 21 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 8 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 11 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 10 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 18 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 98 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 76 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 8 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 118 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| [
-0.6802962422370911,
-0.12786544859409332,
0.12462901324033737,
0.24658456444740295,
-0.24330338835716248,
-0.10035784542560577,
-0.0024491443764418364,
-0.3973338007926941,
0.6456535458564758,
0.5238735675811768,
-0.919205904006958,
-0.8307600617408752,
-0.6968656182289124,
0.489974260330... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
BangumiBase/magithelabyrinthofmagic | BangumiBase | 2023-11-27T01:34:39Z | 0 | 0 | null | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | 2023-11-27T01:34:39Z | 2023-11-26T22:01:03.000Z | 2023-11-26T22:01:03 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Magi - The Labyrinth Of Magic
This is the image base of bangumi Magi - The Labyrinth of Magic, we detected 100 characters, 7708 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 1270 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 16 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 22 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 41 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 183 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 107 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 345 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 68 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 47 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 130 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 58 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 89 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 26 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 26 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 45 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 58 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 59 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 79 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 35 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 24 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 51 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 65 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 90 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 42 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 50 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 40 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 58 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 38 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 64 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 40 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 7 | [Download](30/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 31 | 34 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 44 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 33 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 65 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 79 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 16 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 26 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 15 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 23 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 30 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 162 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 413 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 27 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 24 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 15 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 52 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 25 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 21 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| 49 | 75 | [Download](49/dataset.zip) |  |  |  |  |  |  |  |  |
| 50 | 20 | [Download](50/dataset.zip) |  |  |  |  |  |  |  |  |
| 51 | 188 | [Download](51/dataset.zip) |  |  |  |  |  |  |  |  |
| 52 | 23 | [Download](52/dataset.zip) |  |  |  |  |  |  |  |  |
| 53 | 29 | [Download](53/dataset.zip) |  |  |  |  |  |  |  |  |
| 54 | 55 | [Download](54/dataset.zip) |  |  |  |  |  |  |  |  |
| 55 | 24 | [Download](55/dataset.zip) |  |  |  |  |  |  |  |  |
| 56 | 13 | [Download](56/dataset.zip) |  |  |  |  |  |  |  |  |
| 57 | 36 | [Download](57/dataset.zip) |  |  |  |  |  |  |  |  |
| 58 | 7 | [Download](58/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 59 | 16 | [Download](59/dataset.zip) |  |  |  |  |  |  |  |  |
| 60 | 22 | [Download](60/dataset.zip) |  |  |  |  |  |  |  |  |
| 61 | 28 | [Download](61/dataset.zip) |  |  |  |  |  |  |  |  |
| 62 | 18 | [Download](62/dataset.zip) |  |  |  |  |  |  |  |  |
| 63 | 1272 | [Download](63/dataset.zip) |  |  |  |  |  |  |  |  |
| 64 | 88 | [Download](64/dataset.zip) |  |  |  |  |  |  |  |  |
| 65 | 159 | [Download](65/dataset.zip) |  |  |  |  |  |  |  |  |
| 66 | 15 | [Download](66/dataset.zip) |  |  |  |  |  |  |  |  |
| 67 | 35 | [Download](67/dataset.zip) |  |  |  |  |  |  |  |  |
| 68 | 85 | [Download](68/dataset.zip) |  |  |  |  |  |  |  |  |
| 69 | 21 | [Download](69/dataset.zip) |  |  |  |  |  |  |  |  |
| 70 | 22 | [Download](70/dataset.zip) |  |  |  |  |  |  |  |  |
| 71 | 20 | [Download](71/dataset.zip) |  |  |  |  |  |  |  |  |
| 72 | 15 | [Download](72/dataset.zip) |  |  |  |  |  |  |  |  |
| 73 | 11 | [Download](73/dataset.zip) |  |  |  |  |  |  |  |  |
| 74 | 14 | [Download](74/dataset.zip) |  |  |  |  |  |  |  |  |
| 75 | 15 | [Download](75/dataset.zip) |  |  |  |  |  |  |  |  |
| 76 | 14 | [Download](76/dataset.zip) |  |  |  |  |  |  |  |  |
| 77 | 29 | [Download](77/dataset.zip) |  |  |  |  |  |  |  |  |
| 78 | 14 | [Download](78/dataset.zip) |  |  |  |  |  |  |  |  |
| 79 | 7 | [Download](79/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 80 | 11 | [Download](80/dataset.zip) |  |  |  |  |  |  |  |  |
| 81 | 11 | [Download](81/dataset.zip) |  |  |  |  |  |  |  |  |
| 82 | 16 | [Download](82/dataset.zip) |  |  |  |  |  |  |  |  |
| 83 | 28 | [Download](83/dataset.zip) |  |  |  |  |  |  |  |  |
| 84 | 11 | [Download](84/dataset.zip) |  |  |  |  |  |  |  |  |
| 85 | 11 | [Download](85/dataset.zip) |  |  |  |  |  |  |  |  |
| 86 | 9 | [Download](86/dataset.zip) |  |  |  |  |  |  |  |  |
| 87 | 12 | [Download](87/dataset.zip) |  |  |  |  |  |  |  |  |
| 88 | 89 | [Download](88/dataset.zip) |  |  |  |  |  |  |  |  |
| 89 | 52 | [Download](89/dataset.zip) |  |  |  |  |  |  |  |  |
| 90 | 8 | [Download](90/dataset.zip) |  |  |  |  |  |  |  |  |
| 91 | 21 | [Download](91/dataset.zip) |  |  |  |  |  |  |  |  |
| 92 | 14 | [Download](92/dataset.zip) |  |  |  |  |  |  |  |  |
| 93 | 15 | [Download](93/dataset.zip) |  |  |  |  |  |  |  |  |
| 94 | 10 | [Download](94/dataset.zip) |  |  |  |  |  |  |  |  |
| 95 | 8 | [Download](95/dataset.zip) |  |  |  |  |  |  |  |  |
| 96 | 11 | [Download](96/dataset.zip) |  |  |  |  |  |  |  |  |
| 97 | 60 | [Download](97/dataset.zip) |  |  |  |  |  |  |  |  |
| 98 | 6 | [Download](98/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| noise | 538 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| [
-0.6905638575553894,
-0.10646621137857437,
0.1169368103146553,
0.22335399687290192,
-0.24540430307388306,
-0.06444669514894485,
0.00489277858287096,
-0.3188362419605255,
0.642443060874939,
0.5017232298851013,
-0.9437255263328552,
-0.875213623046875,
-0.6985559463500977,
0.5222271084785461,... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Tamazight-NLP/Pontoon-Translations | Tamazight-NLP | 2023-11-26T23:27:03Z | 0 | 1 | null | [
"task_categories:translation",
"task_categories:text2text-generation",
"size_categories:10K<n<100K",
"language:ber",
"language:zgh",
"language:kab",
"license:mpl-2.0",
"region:us"
] | 2023-11-26T23:27:03Z | 2023-11-26T22:08:41.000Z | 2023-11-26T22:08:41 | ---
license: mpl-2.0
task_categories:
- translation
- text2text-generation
language:
- ber
- zgh
- kab
size_categories:
- 10K<n<100K
pretty_name: Pontoon Translations
---
# Pontoon Translations
This is a dataset containing translations from Mozilla's [Pontoon](https://pontoon.mozilla.org) localization platform for both [Standard Moroccan Tamazight](https://pontoon.mozilla.org/zgh/) and [Taqbaylit](https://pontoon.mozilla.org/kab/).
Source sentences are in English. | [
-0.47593605518341064,
-0.6504351496696472,
0.04325738176703453,
0.7688933610916138,
-0.7605684995651245,
0.29454943537712097,
0.06084249168634415,
-0.07931700348854065,
0.21762077510356903,
0.8908048868179321,
-0.5459853410720825,
-0.6101353168487549,
-0.22839629650115967,
0.04663978889584... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
BangumiBase/vivyfluoriteeyessong | BangumiBase | 2023-11-27T00:32:35Z | 0 | 0 | null | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | 2023-11-27T00:32:35Z | 2023-11-26T22:30:04.000Z | 2023-11-26T22:30:04 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Vivy - Fluorite Eye's Song
This is the image base of bangumi Vivy - Fluorite Eye's Song, we detected 41 characters, 2718 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 16 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 109 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 16 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 987 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 34 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 42 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 32 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 35 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 41 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 30 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 20 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 57 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 43 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 19 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 36 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 99 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 29 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 21 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 48 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 62 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 41 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 53 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 28 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 32 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 29 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 81 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 91 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 48 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 24 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 24 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 12 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 22 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 7 | [Download](32/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 33 | 10 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 27 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 40 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 33 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 33 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 8 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 5 | [Download](39/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 294 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
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vilsonrodrigues/lfw | vilsonrodrigues | 2023-11-27T00:53:06Z | 0 | 0 | null | [
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license: apache-2.0
---
Samples from the LFW dataset. Samples where there is one more face per user were selected. They were then partitioned into two directories: ingestion and recovery. This was done to test a facial recognition system. | [
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seanbethard/service-manuals | seanbethard | 2023-11-27T19:07:57Z | 0 | 0 | null | [
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license: mit
viewer: false
tags:
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multi-train/emb-hotpotqa-train | multi-train | 2023-11-27T01:04:35Z | 0 | 0 | null | [
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configs:
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data_files:
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path: data/train-*
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---
# Dataset Card for "emb-hotpotqa-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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kyomoyo/mini-platypus | kyomoyo | 2023-11-27T01:32:28Z | 0 | 0 | null | [
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multi-train/emb-pubmed | multi-train | 2023-11-27T01:43:39Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T01:43:39Z | 2023-11-27T01:43:16.000Z | 2023-11-27T01:43:16 | ---
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---
# Dataset Card for "emb-pubmed"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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multi-train/emb-medmcqa-train | multi-train | 2023-11-27T01:52:13Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T01:52:13Z | 2023-11-27T01:52:02.000Z | 2023-11-27T01:52:02 | ---
configs:
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---
# Dataset Card for "emb-medmcqa-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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multi-train/emb-record_train | multi-train | 2023-11-27T01:56:21Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T01:56:21Z | 2023-11-27T01:56:12.000Z | 2023-11-27T01:56:12 | ---
configs:
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data_files:
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path: data/train-*
dataset_info:
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splits:
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download_size: 48370504
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---
# Dataset Card for "emb-record_train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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-0.26108306646347046... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
multi-train/emb-scitldr | multi-train | 2023-11-27T02:12:10Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T02:12:10Z | 2023-11-27T02:12:03.000Z | 2023-11-27T02:12:03 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 59114455
num_examples: 1992
download_size: 29584964
dataset_size: 59114455
---
# Dataset Card for "emb-scitldr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.613083004951477,
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-0.5292428135871887,
-0.1033296287059784... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
multi-train/emb-trex-train | multi-train | 2023-11-27T02:26:18Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T02:26:18Z | 2023-11-27T02:24:30.000Z | 2023-11-27T02:24:30 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 2175572925
num_examples: 2284168
download_size: 1321673983
dataset_size: 2175572925
---
# Dataset Card for "emb-trex-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.7096813321113586,
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-0.7524219751358032,
-0.4615170955657959,
-0.17313912510871887,... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
multi-train/emb-triviaqa-train | multi-train | 2023-11-27T02:28:57Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T02:28:57Z | 2023-11-27T02:28:49.000Z | 2023-11-27T02:28:49 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 59025209
num_examples: 52886
download_size: 39225639
dataset_size: 59025209
---
# Dataset Card for "emb-triviaqa-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.7375221252441406,
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-0.29625654220581055,
-0.1428199559450149... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
multi-train/emb-wow-train | multi-train | 2023-11-27T02:31:14Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T02:31:14Z | 2023-11-27T02:31:04.000Z | 2023-11-27T02:31:04 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 112157723
num_examples: 80035
download_size: 65616642
dataset_size: 112157723
---
# Dataset Card for "emb-wow-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.8432875275611877,
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0.4535905718803406,
-1.1182969808578491,
-0.5925339460372925,
-0.4317338168621063,
-0.2665143609046936... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
multi-train/emb-zeroshot-train | multi-train | 2023-11-27T02:31:55Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T02:31:55Z | 2023-11-27T02:31:46.000Z | 2023-11-27T02:31:46 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 131176509
num_examples: 132063
download_size: 75790546
dataset_size: 131176509
---
# Dataset Card for "emb-zeroshot-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.6091876029968262,
-0.3440498113632202,
0.45021694898605347,
0.23721641302108765,
-0.15529915690422058,
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0.3068491518497467,
0.07869178056716919,
0.9952335357666016,
0.3186604082584381,
-1.0442850589752197,
-0.7088332176208496,
-0.44077619910240173,
-0.349538236856... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
nostr-id/raw-sample-toxic-comments-nostr | nostr-id | 2023-11-27T03:15:17Z | 0 | 1 | null | [
"task_categories:text-classification",
"language:en",
"license:cc-by-4.0",
"doi:10.57967/hf/1398",
"region:us"
] | 2023-11-27T03:15:17Z | 2023-11-27T02:32:11.000Z | 2023-11-27T02:32:11 | ---
license: cc-by-4.0
task_categories:
- text-classification
language:
- en
pretty_name: Raw Sample Toxic Comments from Nostr
---
# Introduction
This data were raw sample toxic comments from Nostr classified using [atrifat/hate-speech-detector-api](https://github.com/atrifat/hate-speech-detector-api) and part of [atrifat/nostr-filter-relay](https://github.com/atrifat/nostr-filter-relay) project. This data were solely dedicated for research and initial discussion for detecting toxic comments in Nostr protocol.
# Data Collection
The data were collected between Saturday, November 18, 2023 1:17:18 AM UTC until Monday, November 27, 2023 2:24:25 AM UTC from wss://nostr-id-relay.hf.space relay. wss://nostr-id-relay.hf.space relay aggregates data from top major relays. All data can be collected directly using aggregator relay such as wss://relay.nostr.band or cache relay from Primal.net. The data included in this repository are data which has toxicity probability score greater than or equal to **0.75**.
# Data Structure
The data consist of json separated by lines (jsonl) to separate between each record. Each record has JSON key as follows:
- id: represents Nostr Event ID
- author: represents Nostr author public key
- content: represents original content of author comments
- finalText: represents comments after preprocessing by [atrifat/nostr-filter-relay](https://github.com/atrifat/nostr-filter-relay). finalText were used for classifying toxic comments.
- data: represents toxic classification label, results of automated classification using [atrifat/hate-speech-detector-api](https://github.com/atrifat/hate-speech-detector-api)
# Author
Rif'at Ahdi Ramadhani
# License
[cc-by-4.0](https://creativecommons.org/licenses/by/4.0/)
| [
-0.3045508563518524,
-0.6226754784584045,
0.4405744671821594,
-0.06149650737643242,
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0.03610219433903694,
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0.637988269329071,
-0.5483899116516113,
-0.8886154890060425,
-0.6844459772109985,
0.1657404899597168... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
DataStudio/OCR_UppercaseARIA | DataStudio | 2023-11-27T03:53:04Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T03:53:04Z | 2023-11-27T02:49:28.000Z | 2023-11-27T02:49:28 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 499062262.625
num_examples: 12323
download_size: 498987119
dataset_size: 499062262.625
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
| [
-0.1285339742898941,
-0.18616800010204315,
0.6529127359390259,
0.4943626821041107,
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0.2360742688179016,
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0.7400140166282654,
-0.6508105993270874,
-0.23783984780311584,
-0.7102248668670654,
-0.047826044261455536,... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
malaysia-ai/mosaic-instructions | malaysia-ai | 2023-11-28T08:19:27Z | 0 | 0 | null | [
"language:ms",
"region:us"
] | 2023-11-28T08:19:27Z | 2023-11-27T03:05:24.000Z | 2023-11-27T03:05:24 | ---
language:
- ms
---
# Mosaic format for instructions dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-instructions.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-instructions
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-instructions')
len(dataset)
``` | [
-0.3517948091030121,
-0.3573649823665619,
0.19108708202838898,
0.6830750703811646,
-0.7103549242019653,
-0.12394444644451141,
-0.2771344482898712,
0.15508520603179932,
0.5444760322570801,
0.6261026859283447,
-0.9036481380462646,
-0.5600382089614868,
-0.5619877576828003,
0.23100170493125916... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Cordmail/reddit-NotHowGirlsWork | Cordmail | 2023-11-27T03:08:28Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T03:08:28Z | 2023-11-27T03:07:17.000Z | 2023-11-27T03:07:17 | Entry not found | [
-0.32276472449302673,
-0.22568407654762268,
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0.4346148371696472,
-0.5282984972000122,
0.7012965679168701,
0.7915717363357544,
0.07618629932403564,
0.7746022939682007,
0.2563222646713257,
-0.785281777381897,
-0.22573848068714142,
-0.9104482531547546,
0.5715669393539429,
... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
malaysia-ai/mosaic-extra | malaysia-ai | 2023-11-28T08:13:23Z | 0 | 0 | null | [
"language:ms",
"region:us"
] | 2023-11-28T08:13:23Z | 2023-11-27T03:08:53.000Z | 2023-11-27T03:08:53 | ---
language:
- ms
---
# Mosaic format for extra dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-extra.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-extra
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-extra')
len(dataset)
``` | [
-0.5122454762458801,
-0.17293058335781097,
0.08315365016460419,
0.5341635346412659,
-0.7290666103363037,
0.01665409468114376,
-0.22760994732379913,
-0.004478408023715019,
0.8352839350700378,
0.540865957736969,
-0.6833723783493042,
-0.43067988753318787,
-0.5666132569313049,
0.21802556514739... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
malaysia-ai/mosaic-madlad-400-ms | malaysia-ai | 2023-11-28T08:17:38Z | 0 | 0 | null | [
"language:ms",
"region:us"
] | 2023-11-28T08:17:38Z | 2023-11-27T03:14:00.000Z | 2023-11-27T03:14:00 | ---
language:
- ms
---
# Mosaic format for extra dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-madlad-400-ms.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-madlad-400-ms
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-madlad-400-ms')
len(dataset)
``` | [
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-0.1297205239534378,
0.04155299440026283,
0.6218082904815674,
-0.6221266388893127,
0.024427250027656555,
-0.21383818984031677,
0.04672503098845482,
0.7356026768684387,
0.5481257438659668,
-0.6556257605552673,
-0.4523877799510956,
-0.5493907332420349,
0.2693266272544861,... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
malaysia-ai/mosaic-dedup-text-dataset | malaysia-ai | 2023-11-27T03:14:16Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T03:14:16Z | 2023-11-27T03:14:16.000Z | 2023-11-27T03:14:16 | Entry not found | [
-0.32276472449302673,
-0.22568407654762268,
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-0.5282984972000122,
0.7012965679168701,
0.7915717363357544,
0.07618629932403564,
0.7746022939682007,
0.2563222646713257,
-0.785281777381897,
-0.22573848068714142,
-0.9104482531547546,
0.5715669393539429,
... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
multi-train/emb-reddit-title-body | multi-train | 2023-11-27T06:18:03Z | 0 | 0 | null | [
"region:us"
] | 2023-11-27T06:18:03Z | 2023-11-27T03:33:05.000Z | 2023-11-27T03:33:05 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 95637449375
num_examples: 127445911
download_size: 3302152777
dataset_size: 95637449375
---
# Dataset Card for "emb-reddit-title-body"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.663792610168457,
-0.5154800415039062,
0.45552778244018555,
0.23998408019542694,
-0.3045498728752136,
0.08209352940320969,
0.10161875188350677,
0.052225299179553986,
1.0708622932434082,
0.4579877555370331,
-0.9049416780471802,
-0.9090567827224731,
-0.6407478451728821,
0.08571822941303253... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
malaysia-ai/mosaic-starcoder-filtered | malaysia-ai | 2023-11-28T08:14:20Z | 0 | 0 | null | [
"language:ms",
"region:us"
] | 2023-11-28T08:14:20Z | 2023-11-27T03:47:08.000Z | 2023-11-27T03:47:08 | ---
language:
- ms
---
# Mosaic format for filtered starcoder dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-starcoder.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-starcoder-filtered
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-starcoder-filtered')
len(dataset)
``` | [
-0.5119777321815491,
-0.22383472323417664,
0.08009130507707596,
0.5066901445388794,
-0.7379289269447327,
-0.023987919092178345,
-0.2650659382343292,
0.061838872730731964,
0.6554778218269348,
0.7305667400360107,
-0.6362553834915161,
-0.48812755942344666,
-0.6203331351280212,
0.2724193334579... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
fullneime/pencilbox | fullneime | 2023-11-28T00:05:11Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T00:05:11Z | 2023-11-27T04:01:53.000Z | 2023-11-27T04:01:53 | Entry not found | [
-0.32276472449302673,
-0.22568407654762268,
0.8622258901596069,
0.4346148371696472,
-0.5282984972000122,
0.7012965679168701,
0.7915717363357544,
0.07618629932403564,
0.7746022939682007,
0.2563222646713257,
-0.785281777381897,
-0.22573848068714142,
-0.9104482531547546,
0.5715669393539429,
... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
caichunbing/gaussian_model | caichunbing | 2023-11-28T11:34:13Z | 0 | 0 | null | [
"region:us"
] | 2023-11-28T11:34:13Z | 2023-11-27T04:09:30.000Z | 2023-11-27T04:09:30 | Entry not found | [
-0.32276472449302673,
-0.22568407654762268,
0.8622258901596069,
0.4346148371696472,
-0.5282984972000122,
0.7012965679168701,
0.7915717363357544,
0.07618629932403564,
0.7746022939682007,
0.2563222646713257,
-0.785281777381897,
-0.22573848068714142,
-0.9104482531547546,
0.5715669393539429,
... | null | null | null | null | null | null | null | null | null | null | null | null | null |
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