a simple prompt memo extension

A Deep Learning Python Toolkit for Healthcare Applications.

🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support

A General Causal Inference Framework by Encoding Generative Modeling

A Deep Learning Python Toolkit for Healthcare Applications.

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

oneAPI Threading Building Blocks (oneTBB)

Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

A benchmark of batch-effect correction methods for single-cell RNA sequencing data

[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

A heap memory profiler for Linux

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Official inference library for Mistral models

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

A list of benchmark suites used in the research related to compilers, program performance, scientific computations etc.

A beautiful, simple, clean, and responsive Jekyll theme for academics

🏡 GitHub Pages template for personal academic homepage

Supercharge Your Model Training

The friendly PIL fork

Python logging made (stupidly) simple

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet…

Datasets, Transforms and Models specific to Computer Vision

[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)

Code and documentation for the curation of cellxgene datasets

72.8% MobileNetV2 1.0 model on ImageNet and a spectrum of pre-trained MobileNetV2 models

Simple intermediate representation language for learning and research.