AI Briefing#dataset
The latest AI and developer news about #dataset, with the original source and a short summary.
The latest AI and developer news about #dataset, with the original source and a short summary.
The Hugging Face Hub provides various features for data sharing, including large-scale dataset hosting, a data viewer, and third-party library support.
Hugging Face has launched a SQL Console feature that lets users query datasets directly in the browser.
HuggingFace has released Docmatix, a DocVQA dataset that is 240 times larger than existing ones, containing 2.4 million images and 9.5 million Q/A pairs.
HuggingFace released the SmolLM series of small language models in 135M, 360M, and 1.7B sizes, trained on high-quality data.
Hugging Face has introduced dataset search capabilities by modality, size, format, and library.
Hugging Face unveiled the dataset-building achievements and future plans of the collaborative project 'Data Is Better Together'.
HuggingFace has released JAT, a general-purpose agent capable of performing various tasks, along with its dataset.
A new dataset and leaderboard called 'ConTextual' has been released to evaluate multimodal models' ability to jointly reason over text and images.
Hugging Face and Argilla have unveiled a program that supports building high-quality datasets through community collaboration.
With Renumics Spotlight, you can interactively visualize and analyze Hugging Face datasets with a single line of code.
Hugging Face automatically detects and updates language metadata for datasets using machine learning.
A new feature has been added that allows datasets on Hugging Face Hub to be analyzed directly with SQL via DuckDB.
Databricks and Hugging Face have launched a feature that directly converts Spark dataframes into Hugging Face datasets.
Hugging Face has introduced DOI generation for permanent citation and reproducibility of models and datasets.
New documentation and features for processing audio and image data have been added to the Hugging Face Datasets library.
Includes metadata for over 148,000 playlists and 649,000 tracks, along with Mel spectrograms.
APEACH, a Korean hate speech evaluation dataset generated via crowdsourcing, was released to address the bias and copyright issues of existing web-crawled data.
The Data Measurements Tool, an open-source tool for measuring and comparing dataset quality, has been released.