Datasets

SynData 中文说明 Demo If the video cannot be displayed in your environment, open it directly: assets/syndata-demo.mp4 1. Overview SynData is a next-generation large-scale real-world multimodal dataset newly released by PsiBot. It comprehensively covers key dimensions including vision, language, and action, and provides highly realistic, high-density, and highly usable human data as a solid foundation for embodied intelligence training. Powered by… See the full description on the dataset page: https://huggingface.co/datasets/PsiBotAI/SynData.

I also seperately provide just the prompts in prompts.json keys are the image_id, and the values are the captions generated Captions generated by moondream: vikhyatk/moondream2 Latents generated by SDXL VAE: madebyollin/sdxl-vae-fp16-fix Embeddings generated by SigLIP: hf-hub:timm/ViT-SO400M-14-SigLIP-384 Original dataset: common-canvas/commoncatalog-cc-by Latents f32 and embeddings are f16 bytes Compute cost: 16x3090 for 3 day. Approximately.

This is a large-scale collection of web-crawled documents in 191 world languages, produced by the HPLT project. The source of the data is mostly Internet Archive with some additions from Common Crawl. For a detailed description of the dataset, please refer to https://hplt-project.org/datasets/v2.0 The Cleaned variant of HPLT Datasets v2.0 This is the cleaned variant of the HPLT Datasets v2.0 converted to the Parquet format semi-automatically when being uploaded here. The original JSONL files… See the full description on the dataset page: https://huggingface.co/datasets/jobs-git/HPLT2.0_cleaned.

Introduction Welcome to MLAAD: The Multi-Language Audio Anti-Spoofing Dataset -- a dataset to train, test and evaluate audio deepfake detection. See the paper for more information. License MLAAD is published strictly for non-commercial academic research use, under the CC-BY-NC 4.0 license. Commercial use is not permitted. Download the dataset Option 1: Hugging Face datasets library Install the datasets package: pip install… See the full description on the dataset page: https://huggingface.co/datasets/mueller91/MLAAD.

Dataset Card for "hellaswag" Dataset Summary HellaSwag: Can a Machine Really Finish Your Sentence? is a new dataset for commonsense NLI. A paper was published at ACL2019. Supported Tasks and Leaderboards More Information Needed Languages More Information Needed Dataset Structure Data Instances default Size of downloaded dataset files: 71.49 MB Size of the generated dataset: 65.32 MB Total amount of disk used: 136.81… See the full description on the dataset page: https://huggingface.co/datasets/Rowan/hellaswag.

⚠️ WARNING: This dataset is intended ONLY for reproducing Olmo 3 7B ⚠️ For all other training use cases, including training from scratch, please utilize our primary dolma 3 data mix: https://huggingface.co/datasets/allenai/dolma3_mix-6T. Note: Some olmOCR science PDFs in the current dataset have been redacted following the training of Olmo 3 7B. These texts are indicated with [REMOVED] in the text field. This will affect reproducibility of Olmo 3 7B. For this reason, please use our… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3_mix-6T-1025-7B.

Zyda-2 Zyda-2 is a 5 trillion token language modeling dataset created by collecting open and high quality datasets and combining them and cross-deduplication and model-based quality filtering. Zyda-2 comprises diverse sources of web data, highly educational content, math, code, and scientific papers. To construct Zyda-2, we took the best open-source datasets available: Zyda, FineWeb, DCLM, and Dolma. Models trained on Zyda-2 significantly outperform identical models trained on the… See the full description on the dataset page: https://huggingface.co/datasets/jobs-git/Zyda-2.

Complete Wikipedia dump across all languages. Standard pretraining data source. Structured articles with metadata.

🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens 🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-PDF-CC-2023-06.

Dataset Card for YODAS-Granary Repository: NeMo-speech-data-processor: Granary Paper: Granary: Speech Recognition and Translation Dataset in 25 European Languages Shared by: ESPnet Dataset Description YODAS-Granary is a curated subset of the larger nvidia/Granary dataset, focusing on high-quality pseudo-labeled speech data for Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST) across 23 European languages. Overview… See the full description on the dataset page: https://huggingface.co/datasets/espnet/yodas-granary.

Ettin Pre-training Data Phase 1 of 3: Diverse pre-training data mixture (1.7T tokens) used to train the Ettin model suite. This dataset contains the pre-training phase data used to train all Ettin encoder and decoder models. The data is provided in MDS format ready for use with Composer and the ModernBERT training repository. 📊 Data Composition Data Source Tokens (B) Percentage Description DCLM 837.2 49.1% High-quality web crawl data CC Head 356.6… See the full description on the dataset page: https://huggingface.co/datasets/jhu-clsp/ettin-pretraining-data.

Dataset Card for xP3x Dataset Summary xP3x (Crosslingual Public Pool of Prompts eXtended) is a collection of prompts & datasets across 277 languages & 16 NLP tasks. It contains all of xP3 + much more! It is used for training future contenders of mT0 & BLOOMZ at project Aya @Cohere Labs 🧡 Creation: The dataset can be recreated using instructions available here together with the file in this repository named xp3x_create.py. We provide this version to save processing… See the full description on the dataset page: https://huggingface.co/datasets/CohereLabs/xP3x.

Dataset Card for HuggingFaceFW/finephrase Dataset Summary Synthetic data generated by DataTrove: Model: HuggingFaceTB/SmolLM2-1.7B-Instruct (main) Source dataset: HuggingFaceFW/fineweb-edu, config sample-350BT, split train Generation config: temperature=1.0, top_p=1.0, top_k=50, max_tokens=2048, model_max_context=8192 Speculative decoding: {"method":"suffix","num_speculative_tokens":32} System prompt: None Input column: text Prompt families: faq prompt Rewrite the… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/finephrase.

The dataset of the most popular text-to-image prompts. Dataset Details Dataset Description Curated by: kazimir.ai Funded by [optional]: [More Information Needed] Shared by [optional]: https://kazimir.ai License: apache-2.0 Dataset Sources [optional] Repository: [More Information Needed] Paper [optional]: [More Information Needed] Demo [optional]: [More Information Needed] Uses Free to use. Dataset Structure CSV file… See the full description on the dataset page: https://huggingface.co/datasets/Kazimir-ai/text-to-image-prompts.

LLaVA-OneVision-2-Data Training data for the LLaVA-OneVision-2 multimodal model family, covering large-scale video and spatial reasoning corpora used in mid-training. Dataset Composition Subset Format Description mid_training_video/60s_rest/ WebDataset (.tar) 10,809 shards of ~60s video clips mid_training_video/caption_v0/split_30s.jsonl JSONL Captions for 30-second video clips mid_training_video/caption_v0/split_60s.jsonl JSONL Captions for… See the full description on the dataset page: https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-2-Data.

Dataset Card for OpenAI HumanEval Dataset Summary The HumanEval dataset released by OpenAI includes 164 programming problems with a function sig- nature, docstring, body, and several unit tests. They were handwritten to ensure not to be included in the training set of code generation models. Supported Tasks and Leaderboards Languages The programming problems are written in Python and contain English natural text in comments and docstrings.… See the full description on the dataset page: https://huggingface.co/datasets/openai/openai_humaneval.

About this dataset Context The datasets provided include the players data for the Career Mode from FIFA 15 to FIFA 23. The data allows multiple comparisons for the same players across the last 9 versions of the video game. Some ideas of possible analysis: Historical comparison between Messi and Ronaldo (what skill attributes changed the most during time - compared to real-life stats); Ideal budget to create a competitive team (at the level of top n teams in Europe) and… See the full description on the dataset page: https://huggingface.co/datasets/jsulz/FIFA23.

Dataset Card for SQuAD Dataset Summary Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable. SQuAD 1.1 contains 100,000+ question-answer pairs on 500+ articles. Supported Tasks and Leaderboards Question Answering.… See the full description on the dataset page: https://huggingface.co/datasets/rajpurkar/squad.