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lunaluan/chatbox6_history
lunaluan
2023-11-27T08:21:55Z
0
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null
[ "region:us" ]
2023-11-27T08:21:55Z
2023-11-20T11:04:52.000Z
2023-11-20T11:04:52
Entry not found
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miragepa/Eve
miragepa
2023-11-20T11:24:41Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T11:24:41Z
2023-11-20T11:24:16.000Z
2023-11-20T11:24:16
--- license: openrail ---
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THUDM/BPO
THUDM
2023-11-20T11:49:55Z
0
2
null
[ "task_categories:text-generation", "size_categories:10K<n<100K", "language:en", "license:apache-2.0", "human_feedback", "arxiv:2311.04155", "region:us" ]
2023-11-20T11:49:55Z
2023-11-20T11:46:58.000Z
2023-11-20T11:46:58
--- license: apache-2.0 task_categories: - text-generation language: - en tags: - human_feedback size_categories: - 10K<n<100K pretty_name: BPO --- # Dataset Card for Black-box Prompt Optimization (BPO) ## Dataset Description - **Repository:** https://github.com/thu-coai/BPO - **Paper:** https://arxiv.org/abs/2311.04155 - **Model:** ### Data Summary To advance the development of alignment in language models, we introduce a black-box alignment method. BPO enhances the alignment of various Large Language Models (LLMs) with human preferences using only a plug-and-play model. To further promote alignment work from the prompting perspective, we are releasing the BPO Dataset. This dataset comprises 14,395 entries of prompt optimization pairs, constructed using open-source feedback data with OpenAI's `gpt-3.5-turbo` engine. We have thoroughly ensured the quality and diversity of the data through careful filtering and correction. Please refer to our [paper](https://arxiv.org/abs/2311.04155) for further details. ### Supported Tasks The BPO Dataset is designed for Prompt Optimization / Engineering task. As we have carefully flitered and curated the dataset, it is also a good choice for SFT or RLHF. ### Language The data in BPO are in English. ## Data Structure ### Data Instances An example of "train" looks as follows: ```json { "prompt": "Minimize the following data set\n[3, 4, 6, 7, 8, 10]", "optimized_prompt": "Provide a step-by-step solution to minimize the following data set: [3, 4, 6, 7, 8, 10].", "good_res": "To minimize the values in the given data set, which is a list of numbers, you could sort them in ascending order as follows: [3, 4, 6, 7, 8, 10]. The minimized (least) value in this data set would be 3.", "bad_res": "[3, 4, 6, 7, 8, 10]" } ``` ### Data Fields The data fields are as follows: * `prompt`: the original user input * `optimized_prompt`: the optimized prompt based on feedback * `good_res`: human-chosen (preferred) response * `bad_res`: human-rejected response ### Data Splits | | train | valid | test | |---------------|------:|------:|------:| | BPO | 13895 | 300 | 200 | ## Additional Information ### Source Data Our feedback data come from the following open-sourced datasets: - [OASST1](https://huggingface.co/datasets/OpenAssistant/oasst1) - [hh-rlhf](https://huggingface.co/datasets/Anthropic/hh-rlhf) - [Alpaca-GPT4](https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM/blob/main/data/comparison_data_v2.json) - [Chatbot Arena Conversation](https://huggingface.co/datasets/lmsys/chatbot_arena_conversations) ### Other Known Limitations - Feedback Data Quality: Due to our use of open-source feedback data, some human preferences included may not be entirely accurate. - Task Diversity: Despite our efforts to filter and achieve a diverse dataset, these open-source datasets are clearly not sufficient to cover the wide variety of user queries. - Optimized Prompts: The optimized prompts are auto-generated by `gpt-3.5-turbo` based on feedback data. Even though we have manually reviewed and modified the dataset, we cannot guarantee that all prompt optimizations are correct. ### Citation Information ``` @article{cheng2023black, title={Black-Box Prompt Optimization: Aligning Large Language Models without Model Training}, author={Cheng, Jiale and Liu, Xiao and Zheng, Kehan and Ke, Pei and Wang, Hongning and Dong, Yuxiao and Tang, Jie and Huang, Minlie}, journal={arXiv preprint arXiv:2311.04155}, year={2023} } ```
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Ramyashree/sample-dataset5
Ramyashree
2023-11-20T11:47:45Z
0
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2023-11-20T11:47:45Z
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aisyahhrazak/crawl-soalan
aisyahhrazak
2023-11-20T15:07:21Z
0
0
null
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2023-11-20T15:07:21Z
2023-11-20T11:53:27.000Z
2023-11-20T11:53:27
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nitorogerr/locutor_cristiano_cava
nitorogerr
2023-11-20T11:57:19Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T11:57:19Z
2023-11-20T11:56:52.000Z
2023-11-20T11:56:52
--- license: openrail ---
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sandeshrajx/tom-hiddleston
sandeshrajx
2023-11-20T12:03:28Z
0
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2023-11-20T12:03:28Z
2023-11-20T12:00:24.000Z
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Djacon/ru-izard-emotions
Djacon
2023-11-23T19:17:45Z
0
0
null
[ "task_categories:text-classification", "task_ids:sentiment-classification", "task_ids:multi-class-classification", "task_ids:multi-label-classification", "multilinguality:russian", "size_categories:10K<n<100K", "language:ru", "license:mit", "emotion", "region:us" ]
2023-11-23T19:17:45Z
2023-11-20T12:08:50.000Z
2023-11-20T12:08:50
--- language: - ru license: - mit multilinguality: - russian task_categories: - text-classification task_ids: - sentiment-classification - multi-class-classification - multi-label-classification pretty_name: RuIzardEmotions tags: - emotion size_categories: - 10K<n<100K --- # Dataset Card for RuIzardEmotions ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ### Dataset Summary The RuIzardEmotions dataset is a high-quality translation of the [go-emotions](https://huggingface.co/datasets/go_emotions) dataset and the other [emotion-detection](https://www.kaggle.com/datasets/ishantjuyal/emotions-in-text/data) dataset. It contains 30k Reddit comments labeled for 10 emotion categories (__joy__, __sadness__, __anger__, __enthusiasm__, __surprise__, __disgust__, __fear__, __guilt__, __shame__ and __neutral__). The datasets were translated using the accurate translator [DeepL](https://www.deepl.com/translator) and additional processing. The idea for the dataset was inspired by the [Izard's model](https://en.wikipedia.org/wiki/Differential_Emotions_Scale) of human emotions. The dataset already with predefined train/val/test splits. ### Supported Tasks and Leaderboards This dataset is intended for multi-class, multi-label emotion classification. ### Languages The data is in Russian. ## Dataset Structure ### Data Instances Each instance is a reddit comment with one or more emotion annotations (or neutral). ### Data Splits The simplified data includes a set of train/val/test splits with 24k, 3k, and 3k examples respectively. ## Considerations for Using the Data ### Social Impact of Dataset Emotion detection is a worthwhile problem which can potentially lead to improvements such as better human/computer interaction. However, emotion detection algorithms (particularly in computer vision) have been abused in some cases to make erroneous inferences in human monitoring and assessment applications such as hiring decisions, insurance pricing, and student attentiveness ## Additional Information ### Licensing Information The GitHub repository which houses this dataset has an [Apache License 2.0](https://github.com/Djacon/russian-emotion-detection/blob/main/LICENSE). ### Citation Information ``` @inproceedings{Djacon, author={Djacon}, title={RuIzardEmotions: A Dataset of Fine-Grained Emotions}, year={2023} } ```
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albertcc/test
albertcc
2023-11-22T15:24:18Z
0
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2023-11-22T15:24:18Z
2023-11-20T12:22:40.000Z
2023-11-20T12:22:40
--- license: mit ---
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vsak/Enron_translation_greek
vsak
2023-11-20T20:55:14Z
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FudanSELab/SO_KGXQR_DUPLICATE
FudanSELab
2023-11-20T12:36:44Z
0
0
null
[ "size_categories:1K<n<10K", "language:en", "license:mit", "region:us" ]
2023-11-20T12:36:44Z
2023-11-20T12:30:06.000Z
2023-11-20T12:30:06
--- license: mit dataset_info: - config_name: duplicate_csharp features: - name: query dtype: string - name: relevant sequence: string splits: - name: test num_bytes: 91485 num_examples: 1200 download_size: 61619 dataset_size: 91485 - config_name: duplicate_java features: - name: query dtype: string - name: relevant sequence: string splits: - name: test num_bytes: 102838 num_examples: 1200 download_size: 69239 dataset_size: 102838 - config_name: duplicate_javascript features: - name: query dtype: string - name: relevant sequence: string splits: - name: test num_bytes: 107321 num_examples: 1200 download_size: 69456 dataset_size: 107321 - config_name: duplicate_python features: - name: query dtype: string - name: relevant sequence: string splits: - name: test num_bytes: 109709 num_examples: 1200 download_size: 73833 dataset_size: 109709 configs: - config_name: duplicate_csharp data_files: - split: test path: duplicate_csharp/test-* - config_name: duplicate_java data_files: - split: test path: duplicate_java/test-* - config_name: duplicate_javascript data_files: - split: test path: duplicate_javascript/test-* - config_name: duplicate_python data_files: - split: test path: duplicate_python/test-* language: - en size_categories: - 1K<n<10K --- ## Dataset Description - **Repository:** [GitHub Repository](https://kgxqr.github.io/)
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vsak/YouTube_spam_translation
vsak
2023-11-20T12:43:38Z
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2023-11-20T12:43:38Z
2023-11-20T12:40:01.000Z
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fraviofranco/OptimusPrime
fraviofranco
2023-11-20T12:47:01Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T12:47:01Z
2023-11-20T12:45:41.000Z
2023-11-20T12:45:41
--- license: openrail ---
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vsak/sms_translation_greek
vsak
2023-11-20T12:49:33Z
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2023-11-20T12:49:33Z
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vsak/custom_test_set
vsak
2023-11-20T12:53:40Z
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vsak/youtube_spam_category
vsak
2023-11-20T12:55:41Z
0
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2023-11-20T12:55:41Z
2023-11-20T12:54:09.000Z
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vsak/sms_spam_category
vsak
2023-11-20T13:00:23Z
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2023-11-20T12:59:08.000Z
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vsak/enron_advertisements_cluster
vsak
2023-11-20T13:02:26Z
0
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2023-11-20T13:02:26Z
2023-11-20T13:01:14.000Z
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italovinixius/news-pt
italovinixius
2023-11-20T13:05:27Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-20T13:05:27Z
2023-11-20T13:05:27.000Z
2023-11-20T13:05:27
--- license: apache-2.0 ---
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0ho/llama2
0ho
2023-11-21T09:39:30Z
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null
[ "license:gpl", "region:us" ]
2023-11-21T09:39:30Z
2023-11-20T13:09:13.000Z
2023-11-20T13:09:13
--- license: gpl ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
tfoldi/tesla3_av_rosbags
tfoldi
2023-11-23T07:57:14Z
0
0
null
[ "task_categories:object-detection", "size_categories:100M<n<1B", "license:mit", "rosbag", "ros2", "lidar", "vehicle", "car", "canbus", "autonomous_vehicles", "region:us" ]
2023-11-23T07:57:14Z
2023-11-20T13:27:20.000Z
2023-11-20T13:27:20
--- license: mit task_categories: - object-detection tags: - rosbag - ros2 - lidar - vehicle - car - canbus - autonomous_vehicles pretty_name: tesla3_av_rosbags size_categories: - 100M<n<1B --- # Tesla Model 3 ROS Data Repository ## Overview This repository contains a collection of ROS bag files (in MCAP format) and video streams from a Tesla Model 3 vehicle. It includes data from multiple runs, featuring a variety of sensors such as VLP-16 LiDAR, CAN bus signals, GPS, a 9-axis IMU, and four camera streams. ![image/png](https://cdn-uploads.huggingface.co/production/uploads/655b5b5386fbe7506e2d5feb/YqM5I0xWQlDtVDEl5nPCK.png) ## Dataset Description The data is organized into multiple runs, each containing synchronized streams from the following sensors: * VLP-16 LiDAR: 3D point cloud data capturing the vehicle's surroundings. * CAN Bus: Vehicle's internal communication data including speed, steering angle, and more. * GPS: Geolocation data showing the vehicle's position. * 9-Axis IMU: Inertial data providing acceleration, orientation, and gyroscope measurements. * Camera Streams: Four video streams capturing front, rear, and side views. # License This project is licensed under the MIT License - see the LICENSE file for details. # Contact For any queries or issues, please open an issue in the repository, or contact me directly at tfoldi@starschema.com
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null
null
null
null
null
null
null
null
null
null
null
null
null
FudanSELab/SO_KGXQR_TRAIN
FudanSELab
2023-11-20T16:20:32Z
0
0
null
[ "size_categories:100K<n<1M", "language:en", "license:mit", "region:us" ]
2023-11-20T16:20:32Z
2023-11-20T13:27:26.000Z
2023-11-20T13:27:26
--- license: mit dataset_info: - config_name: duplicate features: - name: question1_id dtype: string - name: question1 dtype: string - name: question2_id dtype: string - name: question2 dtype: string splits: - name: train num_bytes: 2428577 num_examples: 18281 download_size: 1682661 dataset_size: 2428577 - config_name: history features: - name: so_question_id dtype: string - name: question1 dtype: string - name: question2 dtype: string splits: - name: train num_bytes: 10039163 num_examples: 80000 download_size: 7239803 dataset_size: 10039163 - config_name: negative features: - name: question1 dtype: string - name: question2 dtype: string splits: - name: train num_bytes: 27392182 num_examples: 248940 download_size: 11085232 dataset_size: 27392182 - config_name: positive features: - name: question1 dtype: string - name: question2 dtype: string splits: - name: train num_bytes: 11457312 num_examples: 101172 download_size: 7917727 dataset_size: 11457312 configs: - config_name: duplicate data_files: - split: train path: duplicate/train-* - config_name: history data_files: - split: train path: history/train-* - config_name: negative data_files: - split: train path: negative/train-* - config_name: positive data_files: - split: train path: positive/train-* language: - en size_categories: - 100K<n<1M --- ## Dataset Description - **Repository:** [GitHub Repository](https://kgxqr.github.io/)
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null
null
null
null
null
null
null
null
null
null
null
null
null
DamarJati/gpt2-m-storybook
DamarJati
2023-11-21T22:20:27Z
0
0
null
[ "task_categories:text-generation", "language:en", "storybook", "fiction", "region:us" ]
2023-11-21T22:20:27Z
2023-11-20T13:27:42.000Z
2023-11-20T13:27:42
--- language: - en pretty_name: Your Storybook Dataset tags: - storybook - fiction task_categories: - text-generation --- # Your Storybook Dataset Welcome to the repository for the "Your Storybook Dataset." This dataset contains a collection of stories and narratives suitable for various natural language processing tasks. ## Under Collection
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null
null
null
null
null
null
null
null
null
null
null
null
null
ahmedeltaron/yuomm7_data_ft_v2
ahmedeltaron
2023-11-20T14:14:03Z
0
0
null
[ "region:us" ]
2023-11-20T14:14:03Z
2023-11-20T13:28:32.000Z
2023-11-20T13:28:32
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
ryuseiken/PIMPINELA
ryuseiken
2023-11-20T13:54:34Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T13:54:34Z
2023-11-20T13:48:52.000Z
2023-11-20T13:48:52
--- license: openrail ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
severo/test_no_discussions
severo
2023-11-20T14:01:25Z
0
0
null
[ "region:us" ]
2023-11-20T14:01:25Z
2023-11-20T13:59:18.000Z
2023-11-20T13:59:18
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
huggingface-hub-ci/test-dataset-gated
huggingface-hub-ci
2023-11-20T14:03:11Z
0
0
null
[ "region:us" ]
2023-11-20T14:03:11Z
2023-11-20T13:59:45.000Z
2023-11-20T13:59:45
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
ahmedeltaron/testing_reoport_word
ahmedeltaron
2023-11-20T14:15:14Z
0
0
null
[ "region:us" ]
2023-11-20T14:15:14Z
2023-11-20T14:12:41.000Z
2023-11-20T14:12:41
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
Jaspernl/common_voice_13_0_hi_pseudo_labelled
Jaspernl
2023-11-22T09:38:34Z
0
0
null
[ "region:us" ]
2023-11-22T09:38:34Z
2023-11-20T14:14:19.000Z
2023-11-20T14:14:19
--- dataset_info: config_name: nl features: - name: client_id dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: sentence dtype: string - name: up_votes dtype: int64 - name: down_votes dtype: int64 - name: age dtype: string - name: gender dtype: string - name: accent dtype: string - name: locale dtype: string - name: segment dtype: string - name: variant dtype: string - name: whisper_transcript sequence: int64 splits: - name: train num_bytes: 887885645.796 num_examples: 31906 - name: validation num_bytes: 355968997.37 num_examples: 10930 - name: test num_bytes: 402843984.568 num_examples: 10936 download_size: 1643769397 dataset_size: 1646698627.734 configs: - config_name: nl data_files: - split: train path: nl/train-* - split: validation path: nl/validation-* - split: test path: nl/test-* ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
nxsbr/kk
nxsbr
2023-11-24T17:45:48Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-24T17:45:48Z
2023-11-20T14:20:33.000Z
2023-11-20T14:20:33
--- license: openrail ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
wza/finbcf
wza
2023-11-20T14:23:50Z
0
0
null
[ "region:us" ]
2023-11-20T14:23:50Z
2023-11-20T14:23:47.000Z
2023-11-20T14:23:47
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
nourheshamshaheen/ICPR_pipeline3_big
nourheshamshaheen
2023-11-20T14:45:17Z
0
0
null
[ "region:us" ]
2023-11-20T14:45:17Z
2023-11-20T14:38:33.000Z
2023-11-20T14:38:33
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': area '1': heatmap '2': horizontal_bar '3': horizontal_interval '4': line '5': manhattan '6': map '7': pie '8': scatter '9': scatter-line '10': surface '11': venn '12': vertical_bar '13': vertical_box '14': vertical_interval - name: pipeline_label dtype: class_label: names: '0': line '1': other '2': scatter '3': scatter_line '4': vertical_bar - name: true_label dtype: string splits: - name: train num_bytes: 1073939947.25 num_examples: 20630 download_size: 979370224 dataset_size: 1073939947.25 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "ICPR_pipeline3_big" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
null
null
null
null
null
null
null
null
LK0608/video_games_dataset
LK0608
2023-11-28T05:53:15Z
0
0
null
[ "region:us" ]
2023-11-28T05:53:15Z
2023-11-20T14:43:58.000Z
2023-11-20T14:43:58
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
severo/test_big_parquet_file_with_discussion
severo
2023-11-20T14:46:44Z
0
0
null
[ "region:us" ]
2023-11-20T14:46:44Z
2023-11-20T14:44:57.000Z
2023-11-20T14:44:57
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
nourheshamshaheen/ICPR_pipeline3_small
nourheshamshaheen
2023-11-20T14:46:50Z
0
0
null
[ "region:us" ]
2023-11-20T14:46:50Z
2023-11-20T14:45:17.000Z
2023-11-20T14:45:17
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': area '1': heatmap '2': horizontal_bar '3': horizontal_interval '4': line '5': manhattan '6': map '7': pie '8': scatter '9': scatter-line '10': surface '11': venn '12': vertical_bar '13': vertical_box '14': vertical_interval - name: true_label dtype: class_label: names: '0': area '1': heatmap '2': horizontal_bar '3': horizontal_interval '4': manhattan '5': map '6': other '7': pie '8': surface '9': venn '10': vertical_box '11': vertical_interval splits: - name: train num_bytes: 236277245.998 num_examples: 4234 download_size: 216714311 dataset_size: 236277245.998 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "ICPR_pipeline3_small" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
null
null
null
null
null
null
null
null
severo/big_parquet_file_without_discussion
severo
2023-11-20T14:49:13Z
0
0
null
[ "region:us" ]
2023-11-20T14:49:13Z
2023-11-20T14:46:25.000Z
2023-11-20T14:46:25
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
ahmedeltaron/TESTING_only_Title
ahmedeltaron
2023-11-20T14:56:35Z
0
0
null
[ "region:us" ]
2023-11-20T14:56:35Z
2023-11-20T14:56:09.000Z
2023-11-20T14:56:09
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
ahmedeltaron/dataset_tiny_v3_30R
ahmedeltaron
2023-11-20T14:57:58Z
0
0
null
[ "region:us" ]
2023-11-20T14:57:58Z
2023-11-20T14:57:30.000Z
2023-11-20T14:57:30
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
syafie-nzm/crawl-jurnaldbp
syafie-nzm
2023-11-20T15:12:22Z
0
0
null
[ "region:us" ]
2023-11-20T15:12:22Z
2023-11-20T15:11:35.000Z
2023-11-20T15:11:35
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
pavlomospan/common_voice_13_0_hi_pseudo_labelled
pavlomospan
2023-11-20T15:14:16Z
0
0
null
[ "region:us" ]
2023-11-20T15:14:16Z
2023-11-20T15:14:16.000Z
2023-11-20T15:14:16
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
lunaluan/chatbox7_history
lunaluan
2023-11-27T08:22:01Z
0
0
null
[ "region:us" ]
2023-11-27T08:22:01Z
2023-11-20T15:19:52.000Z
2023-11-20T15:19:52
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/csn_php_trainuse_slice1
mengmengmmm
2023-11-20T15:28:35Z
0
0
null
[ "region:us" ]
2023-11-20T15:28:35Z
2023-11-20T15:28:12.000Z
2023-11-20T15:28:12
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/csn_php_trainuse_slice2
mengmengmmm
2023-11-20T15:29:55Z
0
0
null
[ "region:us" ]
2023-11-20T15:29:55Z
2023-11-20T15:29:33.000Z
2023-11-20T15:29:33
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/csn_php_trainuse_slice3
mengmengmmm
2023-11-20T15:31:05Z
0
0
null
[ "region:us" ]
2023-11-20T15:31:05Z
2023-11-20T15:30:43.000Z
2023-11-20T15:30:43
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/csn_php_trainuse_slice4
mengmengmmm
2023-11-20T15:32:08Z
0
0
null
[ "region:us" ]
2023-11-20T15:32:08Z
2023-11-20T15:31:48.000Z
2023-11-20T15:31:48
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/csn_python_trainuse_slice2
mengmengmmm
2023-11-20T15:35:14Z
0
0
null
[ "region:us" ]
2023-11-20T15:35:14Z
2023-11-20T15:34:49.000Z
2023-11-20T15:34:49
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/csn_python_trainuse_slice3
mengmengmmm
2023-11-20T15:36:22Z
0
0
null
[ "region:us" ]
2023-11-20T15:36:22Z
2023-11-20T15:36:00.000Z
2023-11-20T15:36:00
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
lmg-anon/VNTL-1k
lmg-anon
2023-11-20T18:01:58Z
0
0
null
[ "region:us" ]
2023-11-20T18:01:58Z
2023-11-20T15:37:03.000Z
2023-11-20T15:37:03
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 87713571 num_examples: 33746 download_size: 41613063 dataset_size: 87713571 --- # Dataset Card for "VNTL-1k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/csn_python_trainuse_slice4
mengmengmmm
2023-11-20T15:37:33Z
0
0
null
[ "region:us" ]
2023-11-20T15:37:33Z
2023-11-20T15:37:11.000Z
2023-11-20T15:37:11
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
DynamicSuperb/EmotionalSpeechAudioClassification_RAVDESS-EmotionalSound
DynamicSuperb
2023-11-26T17:51:36Z
0
0
null
[ "license:cc-by-nc-sa-4.0", "region:us" ]
2023-11-26T17:51:36Z
2023-11-20T15:46:12.000Z
2023-11-20T15:46:12
--- license: cc-by-nc-sa-4.0 configs: - config_name: default data_files: - split: test path: data/test-* dataset_info: features: - name: file dtype: string - name: audio dtype: audio - name: instruction dtype: string - name: label dtype: string splits: - name: test num_bytes: 598283894.96 num_examples: 1440 download_size: 325216537 dataset_size: 598283894.96 ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/concode_trainuse_slice1
mengmengmmm
2023-11-20T15:48:02Z
0
0
null
[ "region:us" ]
2023-11-20T15:48:02Z
2023-11-20T15:47:44.000Z
2023-11-20T15:47:44
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/concode_trainuse_slice2
mengmengmmm
2023-11-20T15:49:15Z
0
0
null
[ "region:us" ]
2023-11-20T15:49:15Z
2023-11-20T15:48:58.000Z
2023-11-20T15:48:58
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
FlyingFishzzz/des_mesh
FlyingFishzzz
2023-11-20T15:51:31Z
0
0
null
[ "region:us" ]
2023-11-20T15:51:31Z
2023-11-20T15:49:41.000Z
2023-11-20T15:49:41
--- dataset_info: features: - name: target dtype: image - name: prompt dtype: string - name: mesh dtype: image splits: - name: train num_bytes: 520589341.0 num_examples: 1588 download_size: 520482757 dataset_size: 520589341.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "des_mesh" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
null
null
null
null
null
null
null
null
mengmengmmm/concode_trainuse_slice3
mengmengmmm
2023-11-20T15:50:10Z
0
0
null
[ "region:us" ]
2023-11-20T15:50:10Z
2023-11-20T15:49:53.000Z
2023-11-20T15:49:53
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
codeSener/Kaggle-Stable-Diffusion
codeSener
2023-11-20T16:13:29Z
0
0
null
[ "region:us" ]
2023-11-20T16:13:29Z
2023-11-20T16:10:55.000Z
2023-11-20T16:10:55
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
alexdg19/reddit_summaries
alexdg19
2023-11-20T16:17:44Z
0
0
null
[ "region:us" ]
2023-11-20T16:17:44Z
2023-11-20T16:11:05.000Z
2023-11-20T16:11:05
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
jpqueiroz335/vozdoriff
jpqueiroz335
2023-11-20T16:27:04Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T16:27:04Z
2023-11-20T16:26:46.000Z
2023-11-20T16:26:46
--- license: openrail ---
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null
null
null
null
null
null
null
null
null
null
null
null
Jcuhfehl/anna
Jcuhfehl
2023-11-20T17:03:20Z
0
0
null
[ "region:us" ]
2023-11-20T17:03:20Z
2023-11-20T16:52:44.000Z
2023-11-20T16:52:44
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 249782806 num_examples: 507 download_size: 149259532 dataset_size: 249782806 configs: - config_name: default data_files: - split: train path: data/train-* ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
Frixi/Almighty_2019_LaBestia_Era
Frixi
2023-11-20T17:24:56Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T17:24:56Z
2023-11-20T16:56:19.000Z
2023-11-20T16:56:19
--- license: openrail ---
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null
null
null
null
null
null
null
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null
mesolitica/dependency-parsing-instructions
mesolitica
2023-11-22T04:51:04Z
0
0
null
[ "region:us" ]
2023-11-22T04:51:04Z
2023-11-20T16:59:55.000Z
2023-11-20T16:59:55
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
TerminatorJ/localization_dataset
TerminatorJ
2023-11-20T17:00:01Z
0
0
null
[ "region:us" ]
2023-11-20T17:00:01Z
2023-11-20T17:00:01.000Z
2023-11-20T17:00:01
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mesolitica/constituency-parsing-instructions
mesolitica
2023-11-22T04:49:31Z
0
0
null
[ "region:us" ]
2023-11-22T04:49:31Z
2023-11-20T17:00:11.000Z
2023-11-20T17:00:11
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mesolitica/stemming-instructions
mesolitica
2023-11-24T10:13:22Z
0
0
null
[ "region:us" ]
2023-11-24T10:13:22Z
2023-11-20T17:00:21.000Z
2023-11-20T17:00:21
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mesolitica/rumi-jawi-instructions
mesolitica
2023-11-24T02:22:53Z
0
0
null
[ "region:us" ]
2023-11-24T02:22:53Z
2023-11-20T17:00:58.000Z
2023-11-20T17:00:58
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mesolitica/syllable-instructions
mesolitica
2023-11-20T17:01:31Z
0
0
null
[ "region:us" ]
2023-11-20T17:01:31Z
2023-11-20T17:01:31.000Z
2023-11-20T17:01:31
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mesolitica/QA-choice-instructions
mesolitica
2023-11-20T17:03:15Z
0
0
null
[ "region:us" ]
2023-11-20T17:03:15Z
2023-11-20T17:03:15.000Z
2023-11-20T17:03:15
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mesolitica/abstractive-summarization-instructions
mesolitica
2023-11-20T17:03:33Z
0
0
null
[ "region:us" ]
2023-11-20T17:03:33Z
2023-11-20T17:03:33.000Z
2023-11-20T17:03:33
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mesolitica/abstractive-open-QA-instructions
mesolitica
2023-11-20T17:04:13Z
0
0
null
[ "region:us" ]
2023-11-20T17:04:13Z
2023-11-20T17:04:13.000Z
2023-11-20T17:04:13
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
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FudanSELab/SO_KGXQR_HISTORY
FudanSELab
2023-11-20T17:11:05Z
0
0
null
[ "size_categories:1K<n<10K", "language:en", "license:mit", "region:us" ]
2023-11-20T17:11:05Z
2023-11-20T17:04:47.000Z
2023-11-20T17:04:47
--- license: mit dataset_info: - config_name: history_csharp features: - name: so_question_id dtype: string - name: historical_title dtype: string splits: - name: test num_bytes: 133783 num_examples: 2000 download_size: 95916 dataset_size: 133783 - config_name: history_java features: - name: so_question_id dtype: string - name: historical_title dtype: string splits: - name: test num_bytes: 132058 num_examples: 2000 download_size: 93956 dataset_size: 132058 - config_name: history_javascript features: - name: so_question_id dtype: string - name: historical_title dtype: string splits: - name: test num_bytes: 132306 num_examples: 2000 download_size: 91896 dataset_size: 132306 - config_name: history_python features: - name: so_question_id dtype: string - name: historical_title dtype: string splits: - name: test num_bytes: 132390 num_examples: 2000 download_size: 92772 dataset_size: 132390 configs: - config_name: history_csharp data_files: - split: test path: history_csharp/test-* - config_name: history_java data_files: - split: test path: history_java/test-* - config_name: history_javascript data_files: - split: test path: history_javascript/test-* - config_name: history_python data_files: - split: test path: history_python/test-* language: - en size_categories: - 1K<n<10K --- ## Dataset Description - **Repository:** [GitHub Repository](https://kgxqr.github.io/)
[ -0.24821972846984863, 0.12334982305765152, -0.046599503606557846, 0.18349823355674744, -0.38562771677970886, 0.25072988867759705, 0.11216391623020172, 0.4611165225505829, 0.2627774178981781, 0.9756975769996643, -0.6748446822166443, -0.6859074234962463, -0.4914229214191437, -0.1608211100101...
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DataStudio/OCR_Red
DataStudio
2023-11-20T17:33:45Z
0
0
null
[ "region:us" ]
2023-11-20T17:33:45Z
2023-11-20T17:33:30.000Z
2023-11-20T17:33:30
--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 94279480.25 num_examples: 3550 download_size: 94231656 dataset_size: 94279480.25 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
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BangumiBase/kamikazekaitoujeanne
BangumiBase
2023-11-20T18:57:19Z
0
0
null
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
2023-11-20T18:57:19Z
2023-11-20T17:50:43.000Z
2023-11-20T17:50:43
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Kamikaze Kaitou Jeanne This is the image base of bangumi Kamikaze Kaitou Jeanne, we detected 43 characters, 3600 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 | 527 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 39 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 690 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 38 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 33 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 26 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 110 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 23 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 28 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 435 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 351 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 45 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 69 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 14 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 78 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 54 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 21 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 23 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 45 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 18 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 159 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 22 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 103 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 42 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 12 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | 25 | 14 | [Download](25/dataset.zip) | ![preview 1](25/preview_1.png) | ![preview 2](25/preview_2.png) | ![preview 3](25/preview_3.png) | ![preview 4](25/preview_4.png) | ![preview 5](25/preview_5.png) | ![preview 6](25/preview_6.png) | ![preview 7](25/preview_7.png) | ![preview 8](25/preview_8.png) | | 26 | 30 | [Download](26/dataset.zip) | ![preview 1](26/preview_1.png) | ![preview 2](26/preview_2.png) | ![preview 3](26/preview_3.png) | ![preview 4](26/preview_4.png) | ![preview 5](26/preview_5.png) | ![preview 6](26/preview_6.png) | ![preview 7](26/preview_7.png) | ![preview 8](26/preview_8.png) | | 27 | 15 | [Download](27/dataset.zip) | ![preview 1](27/preview_1.png) | ![preview 2](27/preview_2.png) | ![preview 3](27/preview_3.png) | ![preview 4](27/preview_4.png) | ![preview 5](27/preview_5.png) | ![preview 6](27/preview_6.png) | ![preview 7](27/preview_7.png) | ![preview 8](27/preview_8.png) | | 28 | 12 | [Download](28/dataset.zip) | ![preview 1](28/preview_1.png) | ![preview 2](28/preview_2.png) | ![preview 3](28/preview_3.png) | ![preview 4](28/preview_4.png) | ![preview 5](28/preview_5.png) | ![preview 6](28/preview_6.png) | ![preview 7](28/preview_7.png) | ![preview 8](28/preview_8.png) | | 29 | 18 | [Download](29/dataset.zip) | ![preview 1](29/preview_1.png) | ![preview 2](29/preview_2.png) | ![preview 3](29/preview_3.png) | ![preview 4](29/preview_4.png) | ![preview 5](29/preview_5.png) | ![preview 6](29/preview_6.png) | ![preview 7](29/preview_7.png) | ![preview 8](29/preview_8.png) | | 30 | 12 | [Download](30/dataset.zip) | ![preview 1](30/preview_1.png) | ![preview 2](30/preview_2.png) | ![preview 3](30/preview_3.png) | ![preview 4](30/preview_4.png) | ![preview 5](30/preview_5.png) | ![preview 6](30/preview_6.png) | ![preview 7](30/preview_7.png) | ![preview 8](30/preview_8.png) | | 31 | 11 | [Download](31/dataset.zip) | ![preview 1](31/preview_1.png) | ![preview 2](31/preview_2.png) | ![preview 3](31/preview_3.png) | ![preview 4](31/preview_4.png) | ![preview 5](31/preview_5.png) | ![preview 6](31/preview_6.png) | ![preview 7](31/preview_7.png) | ![preview 8](31/preview_8.png) | | 32 | 208 | [Download](32/dataset.zip) | ![preview 1](32/preview_1.png) | ![preview 2](32/preview_2.png) | ![preview 3](32/preview_3.png) | ![preview 4](32/preview_4.png) | ![preview 5](32/preview_5.png) | ![preview 6](32/preview_6.png) | ![preview 7](32/preview_7.png) | ![preview 8](32/preview_8.png) | | 33 | 28 | [Download](33/dataset.zip) | ![preview 1](33/preview_1.png) | ![preview 2](33/preview_2.png) | ![preview 3](33/preview_3.png) | ![preview 4](33/preview_4.png) | ![preview 5](33/preview_5.png) | ![preview 6](33/preview_6.png) | ![preview 7](33/preview_7.png) | ![preview 8](33/preview_8.png) | | 34 | 24 | [Download](34/dataset.zip) | ![preview 1](34/preview_1.png) | ![preview 2](34/preview_2.png) | ![preview 3](34/preview_3.png) | ![preview 4](34/preview_4.png) | ![preview 5](34/preview_5.png) | ![preview 6](34/preview_6.png) | ![preview 7](34/preview_7.png) | ![preview 8](34/preview_8.png) | | 35 | 13 | [Download](35/dataset.zip) | ![preview 1](35/preview_1.png) | ![preview 2](35/preview_2.png) | ![preview 3](35/preview_3.png) | ![preview 4](35/preview_4.png) | ![preview 5](35/preview_5.png) | ![preview 6](35/preview_6.png) | ![preview 7](35/preview_7.png) | ![preview 8](35/preview_8.png) | | 36 | 34 | [Download](36/dataset.zip) | ![preview 1](36/preview_1.png) | ![preview 2](36/preview_2.png) | ![preview 3](36/preview_3.png) | ![preview 4](36/preview_4.png) | ![preview 5](36/preview_5.png) | ![preview 6](36/preview_6.png) | ![preview 7](36/preview_7.png) | ![preview 8](36/preview_8.png) | | 37 | 7 | [Download](37/dataset.zip) | ![preview 1](37/preview_1.png) | ![preview 2](37/preview_2.png) | ![preview 3](37/preview_3.png) | ![preview 4](37/preview_4.png) | ![preview 5](37/preview_5.png) | ![preview 6](37/preview_6.png) | ![preview 7](37/preview_7.png) | N/A | | 38 | 12 | [Download](38/dataset.zip) | ![preview 1](38/preview_1.png) | ![preview 2](38/preview_2.png) | ![preview 3](38/preview_3.png) | ![preview 4](38/preview_4.png) | ![preview 5](38/preview_5.png) | ![preview 6](38/preview_6.png) | ![preview 7](38/preview_7.png) | ![preview 8](38/preview_8.png) | | 39 | 19 | [Download](39/dataset.zip) | ![preview 1](39/preview_1.png) | ![preview 2](39/preview_2.png) | ![preview 3](39/preview_3.png) | ![preview 4](39/preview_4.png) | ![preview 5](39/preview_5.png) | ![preview 6](39/preview_6.png) | ![preview 7](39/preview_7.png) | ![preview 8](39/preview_8.png) | | 40 | 12 | [Download](40/dataset.zip) | ![preview 1](40/preview_1.png) | ![preview 2](40/preview_2.png) | ![preview 3](40/preview_3.png) | ![preview 4](40/preview_4.png) | ![preview 5](40/preview_5.png) | ![preview 6](40/preview_6.png) | ![preview 7](40/preview_7.png) | ![preview 8](40/preview_8.png) | | 41 | 17 | [Download](41/dataset.zip) | ![preview 1](41/preview_1.png) | ![preview 2](41/preview_2.png) | ![preview 3](41/preview_3.png) | ![preview 4](41/preview_4.png) | ![preview 5](41/preview_5.png) | ![preview 6](41/preview_6.png) | ![preview 7](41/preview_7.png) | ![preview 8](41/preview_8.png) | | noise | 109 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
[ -0.7070472836494446, -0.15835605561733246, 0.16921047866344452, 0.2431419938802719, -0.2714865505695343, -0.07666029036045074, -0.04886924475431442, -0.37947309017181396, 0.6609390377998352, 0.5406596064567566, -0.9282427430152893, -0.8718433380126953, -0.705772876739502, 0.492693364620208...
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lmg-anon/VNTL-4k
lmg-anon
2023-11-20T20:42:18Z
0
0
null
[ "region:us" ]
2023-11-20T20:42:18Z
2023-11-20T17:57:09.000Z
2023-11-20T17:57:09
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 87937072 num_examples: 8695 download_size: 0 dataset_size: 87937072 --- # Dataset Card for "VNTL-4k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.6415309309959412, -0.08366604149341583, 0.2595410645008087, 0.16235953569412231, -0.45569875836372375, 0.11291944235563278, 0.46717968583106995, -0.3346943259239197, 0.831342339515686, 0.7093760371208191, -0.7290393710136414, -0.80022794008255, -0.41326704621315, -0.06841714680194855, ...
null
null
null
null
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null
null
null
null
null
null
m111styd4y/marisam
m111styd4y
2023-11-20T18:23:00Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T18:23:00Z
2023-11-20T18:22:18.000Z
2023-11-20T18:22:18
--- license: openrail ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
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null
null
null
null
rkdeva/Dermnet-Test-2
rkdeva
2023-11-20T18:35:12Z
0
0
null
[ "region:us" ]
2023-11-20T18:35:12Z
2023-11-20T18:33:11.000Z
2023-11-20T18:33:11
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: image dtype: image - name: label dtype: string splits: - name: train num_bytes: 376769322.178 num_examples: 3937 download_size: 370140971 dataset_size: 376769322.178 --- # Dataset Card for "Dermnet-Test-2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.49050405621528625, -0.3274669051170349, -0.00008556991815567017, 0.08231420814990997, -0.25286900997161865, -0.1408446878194809, 0.44367891550064087, -0.16196060180664062, 0.6807271242141724, 0.4258868098258972, -0.8232500553131104, -0.6108737587928772, -0.6320401430130005, -0.308984816...
null
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lunaluan/chatbox8_history
lunaluan
2023-11-27T08:22:04Z
0
0
null
[ "region:us" ]
2023-11-27T08:22:04Z
2023-11-20T19:15:14.000Z
2023-11-20T19:15:14
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
sade-adrien/redpajama_v2_32k
sade-adrien
2023-11-20T21:43:44Z
0
0
null
[ "region:us" ]
2023-11-20T21:43:44Z
2023-11-20T19:24:07.000Z
2023-11-20T19:24:07
--- dataset_info: features: - name: raw_content dtype: string - name: doc_id dtype: string - name: meta dtype: string - name: quality_signals dtype: string splits: - name: train num_bytes: 3919516915.1525173 num_examples: 364920 download_size: 18972252318 dataset_size: 3919516915.1525173 --- # Dataset Card for "redpajama_v2_32k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
null
null
null
null
null
null
null
null
wmmarcellino/russian_telegram
wmmarcellino
2023-11-24T17:38:32Z
0
0
null
[ "region:us" ]
2023-11-24T17:38:32Z
2023-11-20T20:47:24.000Z
2023-11-20T20:47:24
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
celsowm/openassistant-llama-style-pt-br
celsowm
2023-11-20T21:06:08Z
0
0
null
[ "region:us" ]
2023-11-20T21:06:08Z
2023-11-20T21:06:01.000Z
2023-11-20T21:06:01
--- dataset_info: features: - name: texto dtype: string splits: - name: train num_bytes: 240447 num_examples: 161 download_size: 152688 dataset_size: 240447 configs: - config_name: default data_files: - split: train path: data/train-* ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
WeStrangeLoops/LHOIPS_EMB
WeStrangeLoops
2023-11-20T21:19:51Z
0
0
null
[ "region:us" ]
2023-11-20T21:19:51Z
2023-11-20T21:10:00.000Z
2023-11-20T21:10:00
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
VishwaV/Plant_disease_dataset
VishwaV
2023-11-20T21:27:19Z
0
0
null
[ "region:us" ]
2023-11-20T21:27:19Z
2023-11-20T21:26:41.000Z
2023-11-20T21:26:41
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mrbmaryam/llama_test_500
mrbmaryam
2023-11-20T21:27:22Z
0
0
null
[ "region:us" ]
2023-11-20T21:27:22Z
2023-11-20T21:27:03.000Z
2023-11-20T21:27:03
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mrbmaryam/mistral_test_500
mrbmaryam
2023-11-20T21:27:58Z
0
0
null
[ "region:us" ]
2023-11-20T21:27:58Z
2023-11-20T21:27:44.000Z
2023-11-20T21:27:44
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
mrbmaryam/zephyr_test_500
mrbmaryam
2023-11-20T21:28:41Z
0
0
null
[ "region:us" ]
2023-11-20T21:28:41Z
2023-11-20T21:28:25.000Z
2023-11-20T21:28:25
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
hayden-donnelly/easy-mnist
hayden-donnelly
2023-11-20T21:45:49Z
0
0
null
[ "task_categories:image-classification", "task_categories:unconditional-image-generation", "size_categories:10K<n<100K", "region:us" ]
2023-11-20T21:45:49Z
2023-11-20T21:31:37.000Z
2023-11-20T21:31:37
--- task_categories: - image-classification - unconditional-image-generation pretty_name: Easy MNIST size_categories: - 10K<n<100K --- # Easy MNIST MNIST processed into three easy to use formats. Each .zip file contains a labels_and_paths.csv file and a data directory. ## mnist_png.zip MNIST in the png format. ``` label path 0 5 data/0.png 1 0 data/1.png 2 4 data/2.png 3 1 data/3.png 4 9 data/4.png ... ... ... 69995 2 data/69995.png 69996 3 data/69996.png 69997 4 data/69997.png 69998 5 data/69998.png 69999 6 data/69999.png ``` ## mnist_numpy.zip MNIST in the npy format. ``` label path 0 5 data/0.npy 1 0 data/1.npy 2 4 data/2.npy 3 1 data/3.npy 4 9 data/4.npy ... ... ... 69995 2 data/69995.npy 69996 3 data/69996.npy 69997 4 data/69997.npy 69998 5 data/69998.npy 69999 6 data/69999.npy ``` ## mnist_numpy_flat.zip MNIST in the npy format, flattened to 784 dimensional vectors. ``` label path 0 5 data/0.npy 1 0 data/1.npy 2 4 data/2.npy 3 1 data/3.npy 4 9 data/4.npy ... ... ... 69995 2 data/69995.npy 69996 3 data/69996.npy 69997 4 data/69997.npy 69998 5 data/69998.npy 69999 6 data/69999.npy ``` ## Acknowledgements - Yann LeCun, Courant Institute, NYU - Corinna Cortes, Google Labs, New York - Christopher J.C. Burges, Microsoft Research, Redmond
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null
null
null
null
null
null
null
null
null
null
null
null
null
Solnauhj/WOLLET
Solnauhj
2023-11-20T21:35:49Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T21:35:49Z
2023-11-20T21:34:13.000Z
2023-11-20T21:34:13
--- license: openrail ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
ElSmoothy/tacos
ElSmoothy
2023-11-20T21:55:30Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-20T21:55:30Z
2023-11-20T21:54:43.000Z
2023-11-20T21:54:43
--- license: apache-2.0 ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
wearemusicai/moisesdb
wearemusicai
2023-11-27T19:36:27Z
0
0
null
[ "language:en", "license:other", "audio", "music", "source separation", "arxiv:2307.15913", "region:us" ]
2023-11-27T19:36:27Z
2023-11-20T22:05:24.000Z
2023-11-20T22:05:24
--- language: - en pretty_name: MoisesDB tags: - audio - music - source separation license: other license_name: ncrlc license_link: https://github.com/moises-ai/moises-db --- # MoisesDB Moises Dataset for Source Separation ### Dataset Description - **Homepage:** [MoisesDB homepage](https://developer.moises.ai/research/) - **Repository:** [MoisesDB repository](https://github.com/moises-ai/moises-db) - **Paper:** [Moisesdb: A dataset for source separation beyond 4-stems](https://arxiv.org/abs/2307.15913) - **Point of Contact:** [Igor Pereira](mailto:igor@moises.ai) ### Dataset Summary MoisesDB is a dataset for source separation. It provides a collection of tracks and their separated stems (vocals, bass, drums, etc.). The dataset is used to evaluate the performance of source separation algorithms. # Download the data Please download the dataset at our research [website](https://developer.moises.ai/research), extract it and configure the environment variable `MOISESDB_PATH` accordingly. ``` export MOISESDB_PATH=./moises-db-data ``` The directory structure should be ``` moisesdb: moisesdb_v0.1 track uuid 0 track uuid 1 . . . ``` # Install You can install this package with ``` pip install git+https://github.com/moises-ai/moises-db.git ``` # Usage ## `MoisesDB` After downloading and configuring the path for the dataset, you can create an instance of `MoisesDB` to access the tracks. You can also provide the dataset path with the `data_path` argument. ``` from moisesdb.dataset import MoisesDB db = MoisesDB( data_path='./moisesdb', sample_rate=44100 ) ``` The `MoisesDB` object has iterator properties that you can use to access all files within the dataset. ``` n_songs = len(db) track = db[0] # Returns a MoisesDBTrack object ``` ## `MoisesDBTrack` The `MoisesDBTrack` object holds information about a track in the dataset, perform on-the-fly mixing for stems and multiple sources within a stem. You can access all the stems and mixture from the `stem` and `audio` properties. The `stem` property returns a dictionary whith available stems as keys and `nd.array` on values. The `audio` property results in a `nd.array` with the mixture. ``` track = db[0] stems = track.stems # stems = {'vocals': ..., 'bass': ..., ...} mixture track.audio # mixture = nd.array ``` The `MoisesDBTrack` object also contains other non-audio information from the track such as: - `track.id` - `track.provider` - `track.artist` - `track.name` - `track.genre` - `track.sources` - `track.bleedings` - `track.activity` The stems and mixture are computed on-the-fly. You can create a stems-only version of the dataset using the `save_stems` method of the `MoisesDBTrack`. ``` track = db[0] path = './moises-db-stems/0' track.save_stems(path) ``` # Performance Evaluation We run a few source separation algorithms as well as oracle methods to evaluate the performance of each track of the `MoisesDB`. These results are located in `csv` files at the `benchmark` folder. # Citing If you used the `MoisesDB` dataset on your research, please cite the following paper. ``` @misc{pereira2023moisesdb, title={Moisesdb: A dataset for source separation beyond 4-stems}, author={Igor Pereira and Felipe Araújo and Filip Korzeniowski and Richard Vogl}, year={2023}, eprint={2307.15913}, archivePrefix={arXiv}, primaryClass={cs.SD} } ``` # Licensing `MoisesDB` is distributed with the NC-RCL license. ``` "Non-Commercial Research Community license (NC-RCL) Limited Redistribution: You are permitted to copy and utilize the provided audio material in any medium or format, as long as it is done only for non-commercial purposes within the research community, and the redistribution is conducted solely through the platform moises.ai or other platforms explicitly authorized by the licensor. Redistribution outside the authorized platforms is not allowed without the licensor's written consent. Attribution: You must give appropriate credit (including the artist's name and the song's title), and provide a link to this license or a notice indicating the terms of this license. Non-Commercial Use: You cannot use the material for any commercial purposes or financial gain. This includes, but is not limited to, the sale, licensing, or rental of the material, as well as any use where the primary aim is to generate revenue or profits. No Derivative Works: You cannot create, remix, adapt, or build upon the material, unless explicitly permitted by the artist. Preservation of Legal Notices: You cannot remove any copyright or other proprietary notices which are included in or attached to the material. Termination: If you fail to comply with this license, your rights to use the material will be terminated automatically. Voice Cloning Restriction: You are prohibited from using the vocal stems or any part of the audio material to create a public digital imitation of the artist's voice (e.g: a vocal clone or replica). This includes, but is not limited to, the utilization of voice synthesis technology, deep learning algorithms, and other artificial intelligence-based tools." ```
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null
null
null
null
null
null
null
null
null
null
null
null
LemTenku/h
LemTenku
2023-11-20T22:13:15Z
0
0
null
[ "region:us" ]
2023-11-20T22:13:15Z
2023-11-20T22:12:52.000Z
2023-11-20T22:12:52
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
Alan318/2
Alan318
2023-11-20T22:14:56Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-20T22:14:56Z
2023-11-20T22:14:56.000Z
2023-11-20T22:14:56
--- license: mit ---
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null
null
null
null
null
null
null
null
null
null
null
null
sade-adrien/redpajama_v2_sample_100M
sade-adrien
2023-11-21T06:00:28Z
0
0
null
[ "region:us" ]
2023-11-21T06:00:28Z
2023-11-20T23:07:38.000Z
2023-11-20T23:07:38
--- dataset_info: features: - name: raw_content dtype: string - name: doc_id dtype: string - name: meta dtype: string - name: quality_signals dtype: string splits: - name: train num_bytes: 1043463774444 num_examples: 100000000 download_size: 226895559008 dataset_size: 1043463774444 --- # Dataset Card for "redpajama_v2_sample_100M" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
null
null
null
null
null
null
null
null
rafa62/renangarcia
rafa62
2023-11-20T23:40:13Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-20T23:40:13Z
2023-11-20T23:38:31.000Z
2023-11-20T23:38:31
--- license: openrail ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
wesleyfaveri/e-test
wesleyfaveri
2023-11-21T02:19:14Z
0
0
null
[ "region:us" ]
2023-11-21T02:19:14Z
2023-11-20T23:50:28.000Z
2023-11-20T23:50:28
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
rashid768/paljer
rashid768
2023-11-23T00:08:27Z
0
0
null
[ "region:us" ]
2023-11-23T00:08:27Z
2023-11-21T00:22:35.000Z
2023-11-21T00:22:35
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
ChaiML/eval_dataset_character_20231108_sample43_response_reselected
ChaiML
2023-11-21T00:26:22Z
0
0
null
[ "region:us" ]
2023-11-21T00:26:22Z
2023-11-21T00:26:20.000Z
2023-11-21T00:26:20
--- dataset_info: features: - name: conversation_id dtype: string - name: bot_id dtype: string - name: user_id dtype: string - name: conversation dtype: string - name: thumbs_up dtype: bool - name: feedback dtype: string - name: model_name dtype: string - name: season dtype: string - name: bot_label dtype: string - name: prompt dtype: string - name: memory dtype: string - name: first_message dtype: string - name: labels dtype: int64 - name: chat_history list: - name: message dtype: string - name: sender dtype: string - name: sample_index dtype: int64 - name: sample_payload list: - name: message dtype: string - name: sender dtype: string - name: sample_response struct: - name: message dtype: string - name: sender dtype: string - name: eval_model_id dtype: string - name: eval_model_output dtype: string - name: eval_model_input dtype: string splits: - name: train num_bytes: 4595702.4 num_examples: 387 download_size: 453380 dataset_size: 4595702.4 --- # Dataset Card for "eval_dataset_character_20231108_sample43_response_reselected" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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null
null
null
null
null
null
null
null
null
null
null
null
null
miragepa/Larin
miragepa
2023-11-21T02:02:29Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-21T02:02:29Z
2023-11-21T00:30:26.000Z
2023-11-21T00:30:26
--- license: openrail ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
prabhjotkaur27/embedded_faqs_medicare_test
prabhjotkaur27
2023-11-21T00:37:46Z
0
0
null
[ "region:us" ]
2023-11-21T00:37:46Z
2023-11-21T00:37:46.000Z
2023-11-21T00:37:46
Entry not found
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null
null
null
null
null
null
null
null
null
null
null
null
null
gagan3012/Numerical_understanding
gagan3012
2023-11-21T00:58:54Z
0
0
null
[ "region:us" ]
2023-11-21T00:58:54Z
2023-11-21T00:58:50.000Z
2023-11-21T00:58:50
--- dataset_info: features: - name: text dtype: string - name: answer dtype: string - name: query dtype: string - name: id dtype: string splits: - name: train num_bytes: 169338670 num_examples: 20875 download_size: 43150062 dataset_size: 169338670 configs: - config_name: default data_files: - split: train path: data/train-* ---
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null
null
null
null
null
null
null
null
null
null
null
null
null
Maljean/State-Sponsored
Maljean
2023-11-21T01:01:01Z
0
0
null
[ "license:unknown", "region:us" ]
2023-11-21T01:01:01Z
2023-11-21T01:01:01.000Z
2023-11-21T01:01:01
--- license: unknown ---
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null
null
null
null
null
null
null
null
null
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null
null
manu/slim-lf
manu
2023-11-21T01:08:42Z
0
0
null
[ "region:us" ]
2023-11-21T01:08:42Z
2023-11-21T01:08:41.000Z
2023-11-21T01:08:41
Entry not found
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null
null
null
null
null
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null
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Maljean/dataset
Maljean
2023-11-21T01:09:42Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-21T01:09:42Z
2023-11-21T01:08:43.000Z
2023-11-21T01:08:43
--- license: apache-2.0 ---
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