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Layer - Neural network inference from the command line, implemented in.

Face recognition library that recognizes and manipulates faces from Python or from the command line.

Library for doing GPR (Gaussian Process Regression) in OCaml. Comes with a command line application.

Neural network inference from the command line, implemented in CHICKEN Scheme.

Serve Llama 2 and other large language models locally from command line or through a browser interface.

Linear Algebra provides AI-assisted learning, courses, tutorials, or study support.

Linear Digressions provides machine-learning models, research, training resources, or evaluation tools.

FastEdit aims to assist developers with injecting fresh and customized knowledge into large language models efficiently using one single command.

Run LLM backends, APIs, frontends, and services with one command.

Poirot

github.com

A macOS app for browsing Claude Code sessions, exploring diffs, and re-running commands. Reads local transcripts, runs offline, open source.

Deploy a ML inference service on a budget in less than 10 lines of code.

Train and run a computer vision model with 5-10 lines of code.

Testing framework dedicated to ML models, from tabular to LLMs. Detect risks of biases, performance issues and errors in 4 lines of code.

AI code reviewer for GitHub Actions or local use, compatible with any LLM and integrated with Jira/Linear.

Generalized linear models in Julia.

Package mat provides implementations of float64 and complex128 matrix structures and linear algebra operations on them.

AI coding assistant offering line-of-code completions and documentation.

LLM App is a Python library that helps you build real-time AI-powered data pipelines with few lines of code.

Distributed linear algebra framework and mathematically expressive Scala DSL.

The Multi-Agent Framework: Given one line requirement, return PRD, design, tasks, repo.

The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo.

A simple Machine Learning Framework written in Swift. Currently features Simple Linear Regression, Polynomial Regression, and Ridge Regression.

No need to keep checking your training, just one import line and you'll know the second it's done.

Speed up your Pandas workflows by changing a single line of code.