eriklindernoren/Action-Recognition

Hugging Face Transformers (huggingface/transformers) is a Python library that centralizes model definitions for text, computer vision, audio, video, and multimodal machine learning, covering both inference and training. The README describes it as a pivot point compatible with training frameworks such as Axolotl, DeepSpeed, and PyTorch-Lightning, and inference engines such as vLLM, SGLang, and TGI, with more than 1M+ model checkpoints listed on the Hugging Face Hub.

LLMs-from-scratch is Sebastian Raschka's GitHub companion to the Manning book Build a Large Language Model (From Scratch), ISBN 9781633437166. It walks through building, pretraining, and finetuning a GPT-style model in PyTorch across seven chapters and five appendices, plus a growing set of bonus notebooks covering newer open architectures.

A high-throughput and memory-efficient inference and serving engine for LLMs

Superpowers is an open-source (MIT) skills library and bootstrap instruction set that turns a coding agent's ad-hoc habits into a fixed pipeline: brainstorm a spec, write a plan, build under TDD, review, then close out the branch. Skills trigger automatically once installed, and the same methodology works across eleven different agent harnesses, each requiring its own install step.