Argilla 2.4: Easily Build Fine-Tuning and Evaluation Datasets on the Hub — No Code Required

Announcing Evaluation on the Hub

Data is better together: Enabling communities to collectively build better datasets together using Argilla and Hugging Face Spaces

MLLM-DataEngine: Closing the Loop of Multimodal Instruction Tuning Data Generation

arXiv:2607. 15299v1 Announce Type: cross Abstract: In this paper, we propose MLLM-DataEngine, a novel closed-loop system that bridges data generation, model training, and evaluation.

ALF: An Active Learning Framework for Scientific Discovery

ALF is a modular active learning framework designed to streamline the entire data acquisition process for scientific discovery. It offers a single API that supports both offline benchmarking against existing datasets and online deployment with an oracle for real‑world candidate acquisition. The framework is open‑source and available on GitHub.

DuckDB: analyze 50,000+ datasets stored on the Hugging Face Hub

Introducing the Data Measurements Tool: an Interactive Tool for Looking at Datasets