Dataset-Tools

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

? Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.

Label Studio is a multi-type data labeling and annotation tool with standardized output format

JavaScript Data Grid / Data Table with a Spreadsheet Look & Feel. Works with React, Angular, and Vue. Supported by the Handsontable team ?

Shared data types for building collaborative software

[CVPR2023] Blur Interpolation Transformer for Real-World Motion from Blur

Etherpad: A modern really-real-time collaborative document editor.

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

pix2tex: Using a ViT to convert images of equations into LaTeX code.

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.