megvii-research/IJCAI2023-CoNR

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.

OpenCV (opencv/opencv) is an open-source C++ library for computer vision, image processing, and deep learning, licensed Apache-2.0 on GitHub. Its GitHub topics list c-plus-plus, computer-vision, deep-learning, image-processing, and opencv, and the project keeps a companion opencv_contrib repository for functionality it doesn't fold into the core. The README itself is oriented around contribution guidelines and community links, including forum.opencv.org, docs.opencv.org/4.x/, and opencv.org/courses, rather than an inline quick-start.

TensorFlow is Google's open-source, end-to-end platform for machine learning, hosted at tensorflow/tensorflow under the Apache-2.0 license. It was originally built within Google Brain's Machine Intelligence team for ML and neural network research, and today it ships stable Python and C++ APIs alongside GPU, CPU-only, and Docker install paths. The README positions it as covering both research work and shipping ML-powered applications.