languagemodels

Why we included this project

This Python package is built for people who want to try large language models without a GPU or a big machine. It runs comfortably in 512MB of RAM, and instead of configuring a heavy transformer stack you call simple functions like lm.do(), lm.complete(), and lm.get_wiki() for instruction following, text completion, and basic retrieval. The author wrote it with learners and educators in mind, and the bundled examples, a CLI chatbot, a Streamlit chat app, and semantic search over documents, are enough to build something real in an afternoon. It also shows useful techniques like int8 quantization and the CTranslate2 backend for fast CPU inference, and you can raise the memory limit to move up to larger models as you get comfortable. If you are teaching LLM concepts or just want to prototype small local inference without a GPU, this is a solid place to start.