LiteRT.js runs machine learning models locally with CPU, GPU and emerging NPU acceleration, potentially reducing server infrastructure, inference charges and data movement.

Browser-based image classification example application using OpenAI CLIP and Transformers.js. Upload images, run zero-shot classification with custom labels directly in the browser, and store images ...

A TypeScript-first library and CLI that turns Markdown into production-ready Word documents: headings, tables, lists, footnotes, images, code blocks with optional syntax highlighting, multi-section ...

Abstract: The eXtreme Multi-label text Classification (XMC) refers to training a classifier that assigns a text sample with relevant labels from an extremely large-scale label set (e.g., millions of ...

Abstract: Prompt-based learning has demonstrated remarkable success in few-shot text classification, outperforming the traditional fine-tuning approach. This method transforms a text input into a ...