ProgramComputer/voxceleb

Genshin Voice Genshin Voice is a dataset of voice lines from the popular game Genshin Impact. Hugging Face 🤗 Genshin-Voice ModelScope Genshin-Voice Per-speaker downloads are grouped by language and ZIP size. Browse every archive in the ZIP index. Last update at 2026-08-13 654252 wavs 7291 without speaker (1%) 52693 without transcription (8%) 1088 without inGameFilename (0%) Dataset Details Dataset Description The dataset contains voice lines… See the full description on the dataset page: https://huggingface.co/datasets/simon3000/genshin-voice.

OMEGA Labs Bittensor Subnet: Multimodal Dataset for AGI Research Introduction The OMEGA Labs Bittensor Subnet Dataset is a groundbreaking resource for accelerating Artificial General Intelligence (AGI) research and development. This dataset, powered by the Bittensor decentralized network, aims to be the world's largest multimodal dataset, capturing the vast landscape of human knowledge and creation. With over 1 million hours of footage and 30 million+ 2-minute… See the full description on the dataset page: https://huggingface.co/datasets/omegalabsinc/omega-multimodal.

all-MiniLM-L6-v2 This is a sentence-transformers(https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. Usage (Sentence-Transformers) Using t...

FLEURS Fleurs is the speech version of the FLoRes machine translation benchmark. We use 2009 n-way parallel sentences from the FLoRes dev and devtest publicly available sets, in 102 languages. Training sets have around 10 hours of supervision. Speakers of the train sets are different than speakers from the dev/test sets. Multilingual fine-tuning is used and ”unit error rate” (characters, signs) of all languages is averaged. Languages and results are also grouped into seven… See the full description on the dataset page: https://huggingface.co/datasets/google/fleurs.

Dataset Card for librispeech_asr Dataset Summary LibriSpeech is a corpus of approximately 1000 hours of 16kHz read English speech, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned. Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for… See the full description on the dataset page: https://huggingface.co/datasets/openslr/librispeech_asr.

Dataset Summary Dataset containing 81,444 pieces of visual art from various artists, taken from WikiArt.org, along with class labels for each image : "artist" : 129 artist classes, including a "Unknown Artist" class "genre" : 11 genre classes, including a "Unknown Genre" class "style" : 27 style classes On WikiArt.org, the description for the "Artworks by Genre" page reads : A genre system divides artworks according to depicted themes and objects. A classical hierarchy of… See the full description on the dataset page: https://huggingface.co/datasets/huggan/wikiart.

Meta Omnilingual ASR Corpus The Omnilingual ASR Corpus is a collection of spontaneous speech recordings and their transcriptions for 348 under-served languages. The corpus was collected as part of Meta FAIR’s Omnilingual ASR project (blog, model, paper) for the purposes of training automatic speech recognition (ASR) and spoken language identification models. Data schema { `language`: "lij_Latn", `iso_639_3`: "lij", `iso_15924`: "Latn"… See the full description on the dataset page: https://huggingface.co/datasets/facebook/omnilingual-asr-corpus.

Dataset Card for CIFAR-10 Dataset Summary The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may… See the full description on the dataset page: https://huggingface.co/datasets/uoft-cs/cifar10.

Dataset Card for Food-101 Dataset Summary This dataset consists of 101 food categories, with 101'000 images. For each class, 250 manually reviewed test images are provided as well as 750 training images. On purpose, the training images were not cleaned, and thus still contain some amount of noise. This comes mostly in the form of intense colors and sometimes wrong labels. All images were rescaled to have a maximum side length of 512 pixels. Supported… See the full description on the dataset page: https://huggingface.co/datasets/ethz/food101.