datasetId large_stringlengths 6 116	author large_stringlengths 2 42	last_modified large_stringdate 2021-04-29 15:34:29 2025-06-05 12:09:07	downloads int64 0 3.97M	tags large listlengths 1 7.92k	task_categories large listlengths 0 48	createdAt large_stringdate 2022-03-02 23:29:22 2025-06-05 10:13:53	trending_score float64 0 40 ⌀	card large_stringlengths 31 1.01M
Allanatrix/Scientific_Research_Tokenized	Allanatrix	2025-06-04T21:09:48Z	43	[ "task_categories:token-classification", "task_categories:text2text-generation", "license:apache-2.0", "size_categories:n<1K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "Science" ]	[ "token-classification", "text2text-generation" ]	2025-04-01T19:14:13Z	null	--- license: apache-2.0 task_categories: - token-classification - text2text-generation pretty_name: Scientific Knowledge condensed size_categories: - n<1K language: - en0 tags: - Science ---
RizhongLin/MNLP_M3_dpo_dataset	RizhongLin	2025-06-04T21:03:57Z	11	[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	[]	2025-06-03T18:02:16Z	null	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: prompt dtype: string - name: chosen dtype: string - name: rejected dtype: string - name: source_project dtype: string - name: domain dtype: string - name: language dtype: string splits: - name: train num_bytes: 340636271.70192444 num_examples: 82615 download_size: 167056504 dataset_size: 340636271.70192444 --- # MNLP_M3_dpo_dataset This dataset contains preference pairs for DPO training. ## Data Sources - M1 Preference Data: Computer Science question answering preferences - HH-RLHF: Human preferences for helpfulness and harmlessness - Stack Exchange Preferences: Preferences from Stack Exchange Q&A platform - UltraFeedback: Human feedback dataset for diverse tasks - SHP: Stanford Human Preferences dataset
momo1942/x_dataset_7834	momo1942	2025-06-04T20:30:49Z	1,113	[ "task_categories:text-classification", "task_categories:token-classification", "task_categories:question-answering", "task_categories:summarization", "task_categories:text-generation", "task_ids:sentiment-analysis", "task_ids:topic-classification", "task_ids:named-entity-recognition", "task_ids:language-modeling", "task_ids:text-scoring", "task_ids:multi-class-classification", "task_ids:multi-label-classification", "task_ids:extractive-qa", "task_ids:news-articles-summarization", "multilinguality:multilingual", "source_datasets:original", "license:mit", "size_categories:100M<n<1B", "region:us" ]	[ "text-classification", "token-classification", "question-answering", "summarization", "text-generation" ]	2025-01-29T01:23:57Z	null	--- license: mit multilinguality: - multilingual source_datasets: - original task_categories: - text-classification - token-classification - question-answering - summarization - text-generation task_ids: - sentiment-analysis - topic-classification - named-entity-recognition - language-modeling - text-scoring - multi-class-classification - multi-label-classification - extractive-qa - news-articles-summarization --- # Bittensor Subnet 13 X (Twitter) Dataset <center> <img src="https://huggingface.co/datasets/macrocosm-os/images/resolve/main/bittensor.png" alt="Data-universe: The finest collection of social media data the web has to offer"> </center> <center> <img src="https://huggingface.co/datasets/macrocosm-os/images/resolve/main/macrocosmos-black.png" alt="Data-universe: The finest collection of social media data the web has to offer"> </center> ## Dataset Description - Repository: momo1942/x_dataset_7834 - Subnet: Bittensor Subnet 13 - Miner Hotkey: 5CkmFXP9s8tnZYB5rv8TvQePmC8Kk5MeqkXP9TKpmwGTYkSf ### Dataset Summary This dataset is part of the Bittensor Subnet 13 decentralized network, containing preprocessed data from X (formerly Twitter). The data is continuously updated by network miners, providing a real-time stream of tweets for various analytical and machine learning tasks. For more information about the dataset, please visit the [official repository](https://github.com/macrocosm-os/data-universe). ### Supported Tasks The versatility of this dataset allows researchers and data scientists to explore various aspects of social media dynamics and develop innovative applications. Users are encouraged to leverage this data creatively for their specific research or business needs. For example: - Sentiment Analysis - Trend Detection - Content Analysis - User Behavior Modeling ### Languages Primary language: Datasets are mostly English, but can be multilingual due to decentralized ways of creation. ## Dataset Structure ### Data Instances Each instance represents a single tweet with the following fields: ### Data Fields - `text` (string): The main content of the tweet. - `label` (string): Sentiment or topic category of the tweet. - `tweet_hashtags` (list): A list of hashtags used in the tweet. May be empty if no hashtags are present. - `datetime` (string): The date when the tweet was posted. - `username_encoded` (string): An encoded version of the username to maintain user privacy. - `url_encoded` (string): An encoded version of any URLs included in the tweet. May be empty if no URLs are present. ### Data Splits This dataset is continuously updated and does not have fixed splits. Users should create their own splits based on their requirements and the data's timestamp. ## Dataset Creation ### Source Data Data is collected from public tweets on X (Twitter), adhering to the platform's terms of service and API usage guidelines. ### Personal and Sensitive Information All usernames and URLs are encoded to protect user privacy. The dataset does not intentionally include personal or sensitive information. ## Considerations for Using the Data ### Social Impact and Biases Users should be aware of potential biases inherent in X (Twitter) data, including demographic and content biases. This dataset reflects the content and opinions expressed on X and should not be considered a representative sample of the general population. ### Limitations - Data quality may vary due to the decentralized nature of collection and preprocessing. - The dataset may contain noise, spam, or irrelevant content typical of social media platforms. - Temporal biases may exist due to real-time collection methods. - The dataset is limited to public tweets and does not include private accounts or direct messages. - Not all tweets contain hashtags or URLs. ## Additional Information ### Licensing Information The dataset is released under the MIT license. The use of this dataset is also subject to X Terms of Use. ### Citation Information If you use this dataset in your research, please cite it as follows: ``` @misc{momo19422025datauniversex_dataset_7834, title={The Data Universe Datasets: The finest collection of social media data the web has to offer}, author={momo1942}, year={2025}, url={https://huggingface.co/datasets/momo1942/x_dataset_7834}, } ``` ### Contributions To report issues or contribute to the dataset, please contact the miner or use the Bittensor Subnet 13 governance mechanisms. ## Dataset Statistics [This section is automatically updated] - Total Instances: 38301266 - Date Range: 2025-01-22T00:00:00Z to 2025-02-13T00:00:00Z - Last Updated: 2025-02-18T21:41:12Z ### Data Distribution - Tweets with hashtags: 46.94% - Tweets without hashtags: 53.06% ### Top 10 Hashtags For full statistics, please refer to the `stats.json` file in the repository. \| Rank \| Topic \| Total Count \| Percentage \| \|------\|-------\|-------------\|-------------\| \| 1 \| NULL \| 20320932 \| 53.06% \| \| 2 \| #riyadh \| 324159 \| 0.85% \| \| 3 \| #zelena \| 227461 \| 0.59% \| \| 4 \| #tiktok \| 174340 \| 0.46% \| \| 5 \| #bbb25 \| 133069 \| 0.35% \| \| 6 \| #ad \| 100664 \| 0.26% \| \| 7 \| #granhermano \| 65946 \| 0.17% \| \| 8 \| #pr \| 52639 \| 0.14% \| \| 9 \| #bbmzansi \| 52388 \| 0.14% \| \| 10 \| #แจกจริง \| 50946 \| 0.13% \| ## Update History \| Date \| New Instances \| Total Instances \| \|------\|---------------\|-----------------\| \| 2025-01-29T01:25:14Z \| 3238156 \| 3238156 \| \| 2025-02-01T13:28:14Z \| 8895127 \| 12133283 \| \| 2025-02-05T01:30:51Z \| 6923889 \| 19057172 \| \| 2025-02-08T13:34:36Z \| 10323931 \| 29381103 \| \| 2025-02-12T01:38:07Z \| 7511126 \| 36892229 \| \| 2025-02-18T06:40:06Z \| 705094 \| 37597323 \| \| 2025-02-18T21:41:12Z \| 703943 \| 38301266 \|
ohjoonhee/UsedCarsImageNet	ohjoonhee	2025-06-04T18:47:58Z	760	["task_categories:image-classification","size_categories:100K<n<1M","format:parquet","modality:image(...TRUNCATED)	[ "image-classification" ]	2025-05-19T06:37:16Z	null	"---\ndataset_info:\n- config_name: cleaned\n features:\n - name: id\n dtype: int64\n - name: (...TRUNCATED)
Kyleyee/eval_set_hh_7b_dpo_true_new	Kyleyee	2025-06-04T18:34:51Z	0	["size_categories:10K<n<100K","format:parquet","modality:text","library:datasets","library:pandas","(...TRUNCATED)	[]	2025-06-04T14:54:33Z	null	"---\ndataset_info:\n features:\n - name: chosen\n dtype: string\n - name: prompt\n dtype: (...TRUNCATED)
zephyr-1111/x_dataset_070287	zephyr-1111	2025-06-04T18:24:14Z	1,103	["task_categories:text-classification","task_categories:token-classification","task_categories:quest(...TRUNCATED)	["text-classification","token-classification","question-answering","summarization","text-generation"(...TRUNCATED)	2025-01-25T07:19:24Z	null	"---\nlicense: mit\nmultilinguality:\n - multilingual\nsource_datasets:\n - original\ntask_categor(...TRUNCATED)
cristiano-sartori/college_computer_science	cristiano-sartori	2025-06-04T16:59:33Z	0	["size_categories:n<1K","format:parquet","modality:text","library:datasets","library:pandas","librar(...TRUNCATED)	[]	2025-06-04T16:59:30Z	null	"---\ndataset_info:\n features:\n - name: question\n dtype: string\n - name: subject\n dtyp(...TRUNCATED)
tsilva/GymnasiumRecording__VizdoomTakeCover_v0	tsilva	2025-06-04T16:42:42Z	0	["size_categories:n<1K","format:parquet","modality:image","library:datasets","library:pandas","libra(...TRUNCATED)	[]	2025-06-04T16:42:40Z	null	"---\ndataset_info:\n features:\n - name: episode_id\n dtype: int64\n - name: image\n dtype(...TRUNCATED)
michael-1111/x_dataset_0205251	michael-1111	2025-06-04T15:59:38Z	884	["task_categories:text-classification","task_categories:token-classification","task_categories:quest(...TRUNCATED)	["text-classification","token-classification","question-answering","summarization","text-generation"(...TRUNCATED)	2025-01-25T07:09:06Z	null	"---\nlicense: mit\nmultilinguality:\n - multilingual\nsource_datasets:\n - original\ntask_categor(...TRUNCATED)
gxy1111/so100_stick	gxy1111	2025-06-04T15:49:59Z	0	["task_categories:robotics","license:apache-2.0","size_categories:10K<n<100K","format:parquet","moda(...TRUNCATED)	[ "robotics" ]	2025-06-04T15:45:03Z	null	"---\nlicense: apache-2.0\ntask_categories:\n- robotics\ntags:\n- LeRobot\n- so100\n- tutorial\nconf(...TRUNCATED)

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Dataset Card for Hugging Face Hub Dataset Cards

This datasets consists of dataset cards for models hosted on the Hugging Face Hub. The dataset cards are created by the community and provide information about datasets hosted on the Hugging Face Hub. This dataset is updated on a daily basis and includes publicly available datasets on the Hugging Face Hub.

This dataset is made available to help support users wanting to work with a large number of Dataset Cards from the Hub. We hope that this dataset will help support research in the area of Dataset Cards and their use but the format of this dataset may not be useful for all use cases. If there are other features that you would like to see included in this dataset, please open a new discussion.

Dataset Details

Uses

There are a number of potential uses for this dataset including:

text mining to find common themes in dataset cards
analysis of the dataset card format/content
topic modelling of dataset cards
training language models on the dataset cards

Out-of-Scope Use

[More Information Needed]

Dataset Structure

This dataset has a single split.

Dataset Creation

Curation Rationale

The dataset was created to assist people in working with dataset cards. In particular it was created to support research in the area of dataset cards and their use. It is possible to use the Hugging Face Hub API or client library to download dataset cards and this option may be preferable if you have a very specific use case or require a different format.

Source Data

The source data is README.md files for datasets hosted on the Hugging Face Hub. We do not include any other supplementary files that may be included in the dataset directory.

Data Collection and Processing

The data is downloaded using a CRON job on a daily basis.

Who are the source data producers?

The source data producers are the creators of the dataset cards on the Hugging Face Hub. This includes a broad variety of people from the community ranging from large companies to individual researchers. We do not gather any information about who created the dataset card in this repository although this information can be gathered from the Hugging Face Hub API.

Annotations [optional]

There are no additional annotations in this dataset beyond the dataset card content.

Annotation process

N/A

Who are the annotators?

N/A

Personal and Sensitive Information

We make no effort to anonymize the data. Whilst we don't expect the majority of dataset cards to contain personal or sensitive information, it is possible that some dataset cards may contain this information. Dataset cards may also link to websites or email addresses.

Bias, Risks, and Limitations

Dataset cards are created by the community and we do not have any control over the content of the dataset cards. We do not review the content of the dataset cards and we do not make any claims about the accuracy of the information in the dataset cards. Some dataset cards will themselves discuss bias and sometimes this is done by providing examples of bias in either the training data or the responses provided by the dataset. As a result this dataset may contain examples of bias.

Whilst we do not directly download any images linked to in the dataset cards, some dataset cards may include images. Some of these images may not be suitable for all audiences.