Datasetpublic

doof-ferb/infore1_25hours

unofficial mirror of InfoRe Technology public dataset №1 official announcement: https://www.facebook.com/groups/j2team.community/permalink/1010834009248719/ 25h, 14.9k samples, InfoRe paid a contractor to read text official download: magnet:?xt=urn:btih:1cbe13fb14a390c852c016a924b4a5e879d85f41&dn=25hours.zip&tr=http%3A%2F%2Foffice.socials.vn%3A8725%2Fannounce mirror: https://files.huylenguyen.com/datasets/infore/25hours.zip unzip password: BroughtToYouByInfoRe pre-process: see… See the full description on the dataset page: https://huggingface.co/datasets/doof-ferb/infore1_25hours.

sourceHugging Facecc-by-4.0updated 1y agoView on Hugging Face

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Dataset Card

unofficial mirror of InfoRe Technology public dataset №1

official announcement: https://www.facebook.com/groups/j2team.community/permalink/1010834009248719/

25h, 14.9k samples, InfoRe paid a contractor to read text

official download: magnet:?xt=urn:btih:1cbe13fb14a390c852c016a924b4a5e879d85f41&dn=25hours.zip&tr=http%3A%2F%2Foffice.socials.vn%3A8725%2Fannounce

mirror: https://files.huylenguyen.com/datasets/infore/25hours.zip

unzip password: BroughtToYouByInfoRe

pre-process: see mycode: https://github.com/phineas-pta/fine-tune-whisper-vi/blob/main/misc/infore1.py

need to do: check misspelling

usage with HuggingFace:

python

# pip install -q "datasets[audio]"
from datasets import load_dataset
from torch.utils.data import DataLoader

dataset = load_dataset("doof-ferb/infore1_25hours", split="train", streaming=True)
dataset.set_format(type="torch", columns=["audio", "transcription"])
dataloader = DataLoader(dataset, batch_size=4)