Machine learning library, Distributed training, Deep learning, Models

Dockfile containing LightGBM, Pytorch and TorchText with GPU Cuda acceleration

🔮 SuperDuper: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search.

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.

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

🔥🔥🔥 A collection of some awesome public CUDA, cuBLAS, TensorRT and High Performance Computing (HPC) projects.

Flops counter for convolutional networks in pytorch framework

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

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

We write your reusable computer vision tools. 💜

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Model performance and tuning analysis conducted on the CIFAR10 and CIFAR100 datasets. Convolutional Neural Network (CNN), Gated Multilayer Perceptron (gMLP), and Vision Transformer (ViT) model architectures are utilized. The study is built using PyTorch, PyTorch Lightning for clean and concise code and Optuna for hyperparameter tuning.

Tools for easing the handoff between AI/ML and App/SRE teams.

Helm charts for creating reproducible and maintainable deployments of Polyaxon with Kubernetes.

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

Accurate Wigner d Recursions in PyTorch

This project aims to develop an image classification system to identify dog breeds using deep learning models. The classifier leverages pre-trained models from the PyTorch library, including ResNet18, AlexNet, and VGG16, to achieve accurate breed identification from images.

Data Science Roadmap from Scratch to Professional

MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.