Language Models

Langflow supports building and deploying agent workflows through a visual development environment.

LLM-API-Key-Proxy provides a gateway for multiple language model APIs, with compatible endpoints and provider translation.

Dust provides a platform for teams to build custom AI agents for work tasks.

ShellGPT brings AI language models to command-line workflows, according to its repository description.

NVIDIA NeMo provides a framework for language, multimodal, and speech AI, including recognition and text to speech.

Petals runs large language models at home through a BitTorrent-style approach and supports text generation and fine-tuning.

This repository lists open language models identified as available for commercial use.

Microsoft’s loralib implements low rank adaptation for large language models.

LLMeBench provides a flexible framework for benchmarking large language models.

PocketPal AI runs language models directly on a phone without requiring a cloud connection.

This guide curates generative AI research updates, interview resources, notebooks, courses, and learning paths.

This project presents a study on improving language model factuality and reasoning through multiagent debate.

Ray provides an AI compute engine with a distributed runtime and libraries for machine learning workloads.

This Lil’Log article explains prompt engineering methods for steering autoregressive language models.

Play Tensor Trust to explore prompt injection attacks and defenses through interactive challenges.

This NBER paper studies language models as both researchers and subjects in automated social science.

For machine learning pipelines, Upgini searches and enriches data with features from public and commercial sources.

OpenLM Arena compares open language models through leaderboards and benchmark results.

CAMEL provides a framework for building and researching systems with multiple AI agents.

A curated list of practical resources about large language models, including examples, papers, and model trees.

Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.

This open book collects methods, tools, and instructions for training, fine-tuning, and running machine learning models.

AgentScale provides business automation solutions using robotic process automation, language models, and AI agents.

Forefront provides a platform for fine tuning and running inference with open source language models.