Language Models

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

Learn about large language models with Hands-On Large Language Models, an illustrated guide featuring more than 275 figures.

Transformer Explainer visualizes how transformer neural networks work through an interactive tool.

The Hugging Face Open LLM Leaderboard compares language models across evaluation tests including IFEval, MATH, and MMLU-Pro.

This bilingual chat language model is described in English and Chinese on the ChatGLM2-6B repository page.

The Hundred-Page Language Models Book teaches machine learning foundations, transformers, and large language models.

DeepLake provides multimodal data infrastructure for AI agents, including retrieval and training.

This repository curates frameworks, libraries, and software for large language models.

This repository provides sample code and notebooks for generative AI on Google Cloud.

Uncover LLM evaluation's importance and explore methods for assessing its performance and impact across industries.

aman.ai publishes course notes and learning materials for Stanford classes in artificial intelligence and deep learning.

SpeechMap.AI compares language models’ refusal rates on controversial speech topics.

txtai combines semantic search, language model orchestration, and AI workflow tools in one framework.

SymbolicAI explores a neurosymbolic approach to large language models.

LangKit monitors language model prompts and responses and extracts signals related to safety and security.

FastDatasets helps create training datasets for large language models.

This guide presents examples of large language models, training, and business adoption.

This repository curates research and resources about multimodal large language models.

TensorRT-LLM provides Python and C++ runtimes with optimizations for language model inference on NVIDIA GPUs.

alphaXiv helps users discover, read, and discuss arXiv papers, with research answers grounded in the underlying work.

Use LLM, a command-line utility and Python library, to interact with large language models.

This repository curates resources for applied AI engineering, including tools and other materials for practitioners.

Stability AI’s StableLM repository contains its language models and related project materials.

AnimatedLLM uses animations to explain the mechanisms behind large language models.