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63990f21cc50af73d29ecfa3 | fka/awesome-chatgpt-prompts | fka | {"license": "cc0-1.0", "tags": ["ChatGPT"], "task_categories": ["question-answering"], "size_categories": ["100K<n<1M"]} | false | null | 2025-01-06T00:02:53 | 8,078 | 78 | false | 68ba7694e23014788dcc8ab5afe613824f45a05c | 🧠 Awesome ChatGPT Prompts [CSV dataset]
This is a Dataset Repository of Awesome ChatGPT Prompts
View All Prompts on GitHub
License
CC-0
| 22,907 | 188,800 | [
"task_categories:question-answering",
"license:cc0-1.0",
"size_categories:n<1K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us",
"ChatGPT"
] | 2022-12-13T23:47:45 | null | null |
6831218309a930f3c0a9e28e | institutional/institutional-books-1.0 | institutional | {"extra_gated_heading": "You need to agree to share your contact information to access this dataset", "extra_gated_description": "## Terms of Use for Early-Access\n\nThis dataset is an Early-Access release shared by the Institutional Data Initiative for research and public-interest use (the \u201cService\u201d). These terms are intended to support experimentation while encouraging collaboration and feedback as we refine the dataset and work with contributing institutions to define shared, long-term norms for open data reuse. To share questions or feedback, contact us at [[email protected]](mailto:[email protected]).\n", "extra_gated_prompt": "**By accessing or downloading the dataset or otherwise using the Service, you agree to the following:**\n\n1. **Noncommercial Use Only** \n You may use the Service solely for **noncommercial purposes**. Open-source projects and other public-use efforts are welcome, even if they may indirectly support commercial use, so long as they are unaffiliated with commercial actors or intent.\n\n If you are affiliated with a commercial organization or plan to use the Service for commercial purposes (including AI model training), you will **contact us first at [[email protected]](mailto:[email protected])**. \n \n2. **No Redistribution** \n You may **not share or redistribute** the Service or any of the data provided through the Service, in whole or in part, including through public repositories or aggregators. If you want others to access it, please direct them to the attribution link.\n\n3. **Derivative Works** \n You may create derivative works for noncommercial use, but you may not make available any such derivative works that substantially reproduce the original dataset. Only outputs that are significantly transformed and cannot substitute for the original\u2014such as evaluations, summary statistics, or visualizations\u2014may be shared, with attribution. \n \n4. **Attribution** \n If you use the dataset in public-facing work, you must include attribution substantially similar to: \n \n *Institutional Books* provided by the Institutional Data Initiative with source material contributed by Harvard Library, available at [https://institutionaldatainitiative.org/institutional-books](https://institutionaldatainitiative.org/institutional-books). \n \n Minor modifications to fit citation style or formatting are permitted, provided the essential elements remain intact.\n\n5. **Provisional Terms** \n These terms apply only to this Early-Access release and may change. We are actively working with contributing institutions to develop a long-term framework for responsible, open data sharing.\n\n6. **DISCLAIMER OF WARRANTY** \n TO THE FULLEST EXTENT PERMITTED BY APPLICABLE LAW, ACCESS TO \u201cSERVICE IS PROVIDED \u201cAS IS\u201d WITHOUT WARRANTY OF ANY KIND (EXPRESS, IMPLIED, OR OTHERWISE), INCLUDING, WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR NONINFRINGEMENT. WE DO NOT WARRANT THAT THE SERVICE WILL OPERATE IN AN UNINTERRUPTED OR ERROR-FREE MANNER OR THAT THE SERVICE IS FREE OF VIRUSES OR OTHER HARMFUL COMPONENTS. WITHOUT LIMITING THE FOREGOING, WE DO NOT WARRANT THAT (A) THE SERVICE WILL MEET YOUR REQUIREMENTS OR EXPECTATIONS OR ACHIEVE THE INTENDED PURPOSES; (B) THE SERVICE WILL NOT EXPERIENCE OUTAGES OR OTHERWISE WILL BE UNINTERRUPTED, TIMELY, OR SECURE; (C) THE INFORMATION OR SERVICES OBTAINED THROUGH OR FROM THE SERVICE WILL BE ACCURATE, COMPLETE, CURRENT, ERROR-FREE, OR RELIABLE; (D) ANY DEFECTS IN OR ON THE SERVICE WILL BE CORRECTED; OR (E) THAT ANY POLLS OR OTHER SOLICITATIONS OF INFORMATION POSTED THROUGH THE SERVICE BY YOU OR OTHER USERS ARE SAFE OR APPROPRIATE FOR YOUR OR OTHER USERS\u2019 PARTICIPATION. WE MAKE NO REPRESENTATION OR WARRANTY REGARDING YOUR ABILITY TO TRANSMIT AND RECEIVE INFORMATION FROM OR THROUGH THE SERVICE, AND YOU AGREE AND ACKNOWLEDGE THAT YOUR ABILITY TO ACCESS THE SERVICE MAY BE IMPAIRED. \n \n7. **LIMITATION OF LIABILITY** \n EXCEPT INSOFAR AS THE FOLLOWING LIMITATION MAY BE PROHIBITED BY APPLICABLE LAW, WE SHALL NOT BE LIABLE TO YOU OR TO ANY THIRD PARTY FOR ANY DIRECT, CONSEQUENTIAL, INDIRECT, PUNITIVE, SPECIAL, OR INCIDENTAL DAMAGES, WHETHER FORESEEABLE OR UNFORESEEABLE (INCLUDING, BUT NOT LIMITED TO, LOSS OF PROFITS OR EARNING POWER, LOSS OF DATA, LOSSES DUE TO ERRORS OR INTERRUPTION IN AVAILABILITY OF THE SERVICE, UNAVAILABILITY OF ANY SERVICE, SERVER, OR COMMUNICATIONS FACILITY, OR DAMAGES DUE TO ACTS OR OMISSIONS OF OTHERS USING THE SERVICE), ARISING OUT OF OR RELATING TO THE SERVICE, INCLUDING WITHOUT LIMITATION YOUR AND OTHERS\u2019 USE OF OR INABILITY TO USE THE SERVICE, OR YOUR RELIANCE UPON INFORMATION OBTAINED FROM OR THROUGH THE SERVICE, WHETHER BASED IN CONTRACT, TORT, STATUTORY, OR OTHER LAW. OUR TOTAL CUMULATIVE LIABILITY TO YOU ARISING OUT OF OR RELATED TO THE SERVICE (INCLUDING, WITHOUT LIMITATION, IN THE WAYS DESCRIBED IN THE PRECEDING SENTENCE), WHETHER BASED IN CONTRACT, TORT, STATUTORY, OR OTHER LAW, WILL NOT EXCEED THE AMOUNT, IF ANY, THAT YOU PAID US TO USE THE SERVICE IN THE TWELVE MONTHS PRECEDING THE CLAIM. THE DISCLAIMERS AND LIMITATIONS SET FORTH IN THIS SECTION SHALL APPLY, TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, WHETHER OR NOT WE HAVE BEEN NEGLIGENT OR OTHERWISE AT FAULT. \n YOU ACKNOWLEDGE THAT, FOR PURPOSES OF THE FOREGOING DISCLAIMERS AND LIMITATIONS, AS WELL AS THE INDEMNITY PROVISION IN SECTION 8 BELOW, THE TERMS \u201cWE,\u201d \u201cOUR,\u201d \u201cUS,\u201d \u201cINSTITUTIONAL DATA INITIATIVE,\u201d AND \u201cIDI\u201d INCLUDE THE CORPORATE BODY PRESIDENT AND FELLOWS OF HARVARD COLLEGE, ALSO KNOWN AS HARVARD UNIVERSITY, AND ITS VARIOUS SCHOOLS, THE MEMBERS OF ITS GOVERNING BOARDS, AND ITS OFFICERS, FACULTY MEMBERS, EMPLOYEES, FELLOWS, AND TO THE EXTENT WORKING ON IDI, ITS STUDENTS, CONTRACTORS, AND REPRESENTATIVES. \n8. **Indemnification** \n You agree to indemnify us and hold us harmless from any and all claims, liabilities, damages, losses and expenses, including reasonable attorneys\u2019 fees and costs, relating to or arising out of (a) your use or attempted use of the Service in violation of these Terms of Service; or (b) your violation of any law or rights of any third party in connection with your use of the Service. \n \n9. **Governing Law/ Jurisdiction** \n You agree that the Terms of Service and any claim or dispute arising out of or relating to the Service or Terms of Service will be governed by the laws of the Commonwealth of Massachusetts, excluding its conflicts of laws principles. You agree that all such claims and disputes will be heard and resolved exclusively in the federal or state courts located in and serving Middlesex or Suffolk County, Massachusetts, U.S.A. You consent to the personal jurisdiction of those courts over you for this purpose, and you waive and agree not to assert any objection to such proceedings in those courts (including any defense or objection of lack of proper jurisdiction or inconvenience of forum). \n \n10. **Whole Agreement/ Amendment** \n These Terms of Service constitute the entire agreement between you and Harvard with respect to your use of the Service. We reserve the right to amend these Terms of Service at any time. The Service will post notice of changes to the terms on this webpage, and by accessing the Service after modifications to these Terms of Service have been posted, you agree to be bound by all the modified terms. Accordingly, you should periodically revisit this page to review the then-current Terms of Service. \n \n", "extra_gated_fields": {"I accept the noncommercial IDI Terms of Use for Early-Access and will not redistribute the dataset": "checkbox"}, "dataset_info": {"features": [{"name": "barcode_src", "dtype": "string"}, {"name": "title_src", "dtype": "string"}, {"name": "author_src", "dtype": "string"}, {"name": "date1_src", "dtype": "string"}, {"name": "date2_src", "dtype": "string"}, {"name": "date_types_src", "dtype": "string"}, {"name": "page_count_src", "dtype": "int32"}, {"name": "token_count_o200k_base_gen", "dtype": "int32"}, {"name": "language_src", "dtype": "string"}, {"name": "language_gen", "dtype": "string"}, {"name": "language_distribution_gen", "sequence": [{"name": "language", "dtype": "string"}, {"name": "proportion", "dtype": "float64"}]}, {"name": "topic_or_subject_src", "dtype": "string"}, {"name": "topic_or_subject_gen", "dtype": "string"}, {"name": "topic_or_subject_score_gen", "dtype": "float64"}, {"name": "genre_or_form_src", "dtype": "string"}, {"name": "general_note_src", "dtype": "string"}, {"name": "ocr_score_src", "dtype": "int32"}, {"name": "ocr_score_gen", "dtype": "int32"}, {"name": "likely_duplicates_barcodes_gen", "sequence": "string"}, {"name": "text_analysis_gen", "struct": [{"name": "text_by_page_gen", "struct": [{"name": "tokenizability_score", "dtype": "float64"}, {"name": "char_count", "dtype": "int32"}, {"name": "word_count", "dtype": "int32"}, {"name": "word_count_unique", "dtype": "int32"}, {"name": "word_type_token_ratio", "dtype": "float64"}, {"name": "bigram_count", "dtype": "int32"}, {"name": "bigram_count_unique", "dtype": "int32"}, {"name": "bigram_type_token_ratio", "dtype": "float64"}, {"name": "trigram_count", "dtype": "int32"}, {"name": "trigram_count_unique", "dtype": "int32"}, {"name": "trigram_type_token_ratio", "dtype": "float64"}, {"name": "sentence_count", "dtype": "int32"}, {"name": "sentence_count_unique", "dtype": "int32"}]}, {"name": "text_by_page_src", "struct": [{"name": "tokenizability_score", "dtype": "float64"}, {"name": "char_count", "dtype": "int32"}, {"name": "word_count", "dtype": "int32"}, {"name": "word_count_unique", "dtype": "int32"}, {"name": "word_type_token_ratio", "dtype": "float64"}, {"name": "bigram_count", "dtype": "int32"}, {"name": "bigram_count_unique", "dtype": "int32"}, {"name": "bigram_type_token_ratio", "dtype": "float64"}, {"name": "trigram_count", "dtype": "int32"}, {"name": "trigram_count_unique", "dtype": "int32"}, {"name": "trigram_type_token_ratio", "dtype": "float64"}, {"name": "sentence_count", "dtype": "int32"}, {"name": "sentence_count_unique", "dtype": "int32"}]}]}, {"name": "identifiers_src", "struct": [{"name": "lccn", "sequence": "string"}, {"name": "isbn", "sequence": "string"}, {"name": "ocolc", "sequence": "string"}]}, {"name": "hathitrust_data_ext", "struct": [{"name": "url", "dtype": "string"}, {"name": "rights_code", "dtype": "string"}, {"name": "reason_code", "dtype": "string"}, {"name": "last_check", "dtype": "string"}]}, {"name": "text_by_page_src", "sequence": "large_string"}, {"name": "text_by_page_gen", "sequence": "large_string"}]}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | false | null | 2025-06-16T13:38:17 | 202 | 46 | false | d2f504a112fa057ddd2bc536188535a674a90270 |
📚 Institutional Books 1.0
Institutional Books is a growing corpus of public domain books. This 1.0 release is comprised of 983,004 public domain books digitized as part of Harvard Library's participation in the Google Books project and refined by the Institutional Data Initiative. Use of this data is governed by the IDI Terms of Use for Early-Access.
983K books, published largely in the 19th and 20th centuries
242B o200k_base tokens
386M pages of text, available in both original… See the full description on the dataset page: https://huggingface.co/datasets/institutional/institutional-books-1.0. | 38,186 | 38,308 | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2506.08300",
"region:us"
] | 2025-05-24T01:31:47 | null | null |
6858e379f9dc599076596798 | facebook/seamless-interaction | facebook | {"license": "cc-by-nc-4.0", "configs": [{"config_name": "improvised", "data_files": [{"split": "dev", "path": ["improvised/dev/**/*"]}, {"split": "test", "path": ["improvised/test/**/*"]}, {"split": "train", "path": ["improvised/train/**/*"]}]}, {"config_name": "naturalistic", "data_files": [{"split": "dev", "path": ["naturalistic/dev/**/*"]}, {"split": "test", "path": ["naturalistic/test/**/*"]}, {"split": "train", "path": ["naturalistic/train/**/*"]}]}], "tags": ["webdataset", "audio", "video"], "pretty_name": "Seamless Interaction"} | false | null | 2025-06-27T15:55:31 | 41 | 41 | false | 4632fa0baced57b691df6ceecca406109f5ceeae |
Seamless Interaction Dataset
A large-scale multimodal dataset of 4,000+ hours of human interactions for AI research
🖼️ Blog
🌐 Website
🎮 Demo
📦 GitHub
📄 Paper
Human communication involves a complex interplay of verbal and nonverbal signals, essential for conveying meaning and achieving interpersonal goals.
The Seamless Interaction Dataset is a large-scale collection of over 4,000 hours of face-to-face interaction footage from more than 4,000 participants in… See the full description on the dataset page: https://huggingface.co/datasets/facebook/seamless-interaction. | 1 | 1 | [
"license:cc-by-nc-4.0",
"modality:audio",
"modality:video",
"library:webdataset",
"region:us",
"webdataset",
"audio",
"video"
] | 2025-06-23T05:17:45 | null | null |
684fcd62078845bb1392efc1 | FreedomIntelligence/ShareGPT-4o-Image | FreedomIntelligence | {"license": "apache-2.0", "language": ["en"], "tags": ["GPT-4o-Image-Generation"], "task_categories": ["text-to-image", "image-to-image"], "size_categories": ["10K<n<100K"], "configs": [{"config_name": "1_text_to_image", "data_files": "text_to_image.json"}, {"config_name": "2_text_and_image_to_image", "data_files": "text_and_image_to_image.json"}]} | false | null | 2025-06-28T03:03:11 | 39 | 39 | false | bad66a9a0b4595795f5ab77866cf0beee593d1ff |
📚 ShareGPT-4o-Image
ShareGPT-4o-Image is a large-scale and high-quality image generation dataset, where all images are produced by GPT-4o’s image generation capabilities. This dataset is designed to align open multimodal models with GPT-4o’s strengths in visual content creation. It includes 45K text-to-image and 46K text-and-image-to-image samples, making it a useful resource for enhancing multimodal models in both image generation and editing tasks.
⚠️ Statement:… See the full description on the dataset page: https://huggingface.co/datasets/FreedomIntelligence/ShareGPT-4o-Image. | 75 | 75 | [
"task_categories:text-to-image",
"task_categories:image-to-image",
"language:en",
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2506.18095",
"region:us",
"GPT-4o-Image-Generation"
] | 2025-06-16T07:53:06 | null | null |
6851cac31458ae6b02f8e8e7 | EssentialAI/essential-web-v1.0 | EssentialAI | {"license": "odc-by", "size_categories": ["10B<n<100B"]} | false | null | 2025-06-22T18:39:56 | 166 | 39 | false | 446921a298bb7604cb4cf22e921540d67ffcd061 |
🌐 Essential-Web: Complete 24-Trillion Token Dataset
🏆 Website | 🖥️ Code | 📖 Paper
📋 Dataset Description
Essential-Web is a 24-trillion-token web dataset with document-level metadata designed for flexible dataset curation. The dataset provides metadata including subject matter classification, web page type, content complexity, and document quality scores for each of the 23.6 billion documents.
Researchers can filter and curate specialized datasets using the… See the full description on the dataset page: https://huggingface.co/datasets/EssentialAI/essential-web-v1.0. | 75,487 | 75,487 | [
"license:odc-by",
"size_categories:10B<n<100B",
"arxiv:2506.14111",
"region:us"
] | 2025-06-17T20:06:27 | null | null |
685bd0388531af7984c4c29e | OpenGVLab/MMBench-GUI | OpenGVLab | {"license": "apache-2.0"} | false | null | 2025-06-25T13:55:30 | 25 | 25 | false | 925c909d98d53b90a6c013e61d746bb6f73bcf93 |
🖥️ MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents
Introduction
We are happy to release MMBench-GUI, a hierarchical, multi-platform benchmark framework and toolbox, to evaluate GUI agents. MMBench-GUI is comprising four evaluation levels: GUI Content Understanding, GUI Element Grounding, GUI Task Automation, and GUI Task Collaboration. We also propose the Efficiency–Quality Area (EQA) metric for agent navigation, integrating… See the full description on the dataset page: https://huggingface.co/datasets/OpenGVLab/MMBench-GUI. | 0 | 0 | [
"license:apache-2.0",
"region:us"
] | 2025-06-25T10:32:24 | null | null |
6751d39f333cc16b83338960 | HuggingFaceFW/fineweb-2 | HuggingFaceFW | "{\"license\": \"odc-by\", \"task_categories\": [\"text-generation\"], \"language\": [\"aai\", \"aak(...TRUNCATED) | false | null | 2025-06-27T00:43:27 | 519 | 24 | false | a8a99b128121a41b17d95901715603386f6b1daf | "\n\t\n\t\t\n\t\t🥂 FineWeb2\n\t\n\n\n \n\n\n\nA sparkling update with 1000s of languages\n\n\n(...TRUNCATED) | 38,340 | 422,078 | ["task_categories:text-generation","language:aai","language:aak","language:aau","language:aaz","lang(...TRUNCATED) | 2024-12-05T16:23:59 | null | null |
685316c9c83fc57866d95170 | yandex/mad-cars | yandex | "{\"license\": \"cc-by-nc-sa-4.0\", \"size_categories\": [\"1M<n<10M\"], \"pretty_name\": \"Multi-vi(...TRUNCATED) | false | null | 2025-06-29T09:23:25 | 24 | 24 | false | 3fa6f91824d0164029908d7953a1b0483adc38ba | "\n\t\n\t\t\n\t\tMAD-Cars: Multi-view Auto Dataset 🚗\n\t\n\n\n\t\n\t\t\n\t\tDataset Description\n(...TRUNCATED) | 10 | 10 | ["task_categories:image-to-video","license:cc-by-nc-sa-4.0","size_categories:1M<n<10M","format:csv",(...TRUNCATED) | 2025-06-18T19:43:05 | null | null |
68509b3a56e1e818c1f667bc | nvidia/AceReason-1.1-SFT | nvidia | "{\"language\": [\"en\"], \"license\": \"cc-by-4.0\", \"tags\": [\"nvidia\", \"reasoning\", \"math\"(...TRUNCATED) | false | null | 2025-06-18T19:01:52 | 50 | 23 | false | 5ac692742de9f2481f8274d022dc78d5fc96c249 | "\n\t\n\t\t\n\t\tAceReason-1.1-SFT\n\t\n\n\n\n\n\n\n\n\n\n\nAceReason-1.1-SFT is a diverse and high-(...TRUNCATED) | 2,954 | 2,954 | ["task_categories:text-generation","language:en","license:cc-by-4.0","size_categories:1M<n<10M","for(...TRUNCATED) | 2025-06-16T22:31:22 | null | null |
683f515179507863731aaf8c | nvidia/OpenScience | nvidia | "{\"configs\": [{\"config_name\": \"OS-Q3-235B-4\", \"data_files\": [{\"split\": \"train\", \"path\"(...TRUNCATED) | false | null | 2025-06-18T19:21:21 | 33 | 19 | false | 7bd0437e4756f761768fe7e5cebeaa75480a4fd6 | "\n\t\n\t\t\n\t\tDataset Description:\n\t\n\nOpenScience is a multi-domain synthetic dataset designe(...TRUNCATED) | 435 | 435 | ["license:cc-by-4.0","size_categories:1M<n<10M","format:json","modality:text","library:datasets","li(...TRUNCATED) | 2025-06-03T19:47:29 | null | null |
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