Explain any ML models anywhere

Explain any ML models anywhere

Framework-agnostic utilities for loading and running ML models in the browser via WebGPU/WASM

Construct AI & ML models with JSON using Typescript & Tensorflow

Deploy ML models to production

Construct AI & ML models with JSON using Typescript & Tensorflow

Generate Tensorflow model with JSON. A Declarative JSON library for AI, NLP and ML models powered by tensorflow

Construct AI & ML models with JSON using Typescript & Tensorflow

An open-source machine learning framework.

Static and dynamic vulnerability scanner for ML models and pipelines

Core types and classes for Google services.

ml-learn is a straightforward JS library to train ML models on your JSON data

ObelyZK CLI — prove ML models and verify on Starknet from your terminal

Splitifi Intelligence MCP — outcome predictions, judge profiles, and legal workflows powered by 29,211 production ML models trained on real court records. Serves litigants, attorneys, judges, mediators, CDFAs, and litigation funders.

Run inference on Hugging Face open ML models for NLP, vision, and audio tasks.

Official CLI for Cirron, providing streamlined commands for building, deploying, and managing ML models on and off the platform.

A Javascript library for running ONNX models on browsers

Autonomous ML research harness for Claude Code. The autoresearch loop as a formal protocol — iteratively trains, evaluates, and improves ML models with structured experiment tracking, convergence detection, immutable evaluation infrastructure, and safety

Native face embedding using ML models

Matrix manipulation and computation library